From 9a1cc06ebe8039ee5be508f4bade8e038c1a31e8 Mon Sep 17 00:00:00 2001
From: Leszek Swirski <leszek@swirski.co.uk>
Date: Tue, 21 May 2013 17:53:36 +0100
Subject: [PATCH 01/27] Fix pixel value rendering for non-fixed-size QT windows

---
 modules/highgui/src/window_QT.cpp | 71 +++++++++++++++----------------
 1 file changed, 35 insertions(+), 36 deletions(-)

diff --git a/modules/highgui/src/window_QT.cpp b/modules/highgui/src/window_QT.cpp
index 50f2b9e787..438c356f73 100644
--- a/modules/highgui/src/window_QT.cpp
+++ b/modules/highgui/src/window_QT.cpp
@@ -2651,17 +2651,16 @@ void DefaultViewPort::paintEvent(QPaintEvent* evnt)
     //Now disable matrixWorld for overlay display
     myPainter.setWorldMatrixEnabled(false);
 
+    //overlay pixel values if zoomed in far enough
+    if (param_matrixWorld.m11()*ratioX >= threshold_zoom_img_region &&
+        param_matrixWorld.m11()*ratioY >= threshold_zoom_img_region)
+    {
+        drawImgRegion(&myPainter);
+    }
+
     //in mode zoom/panning
     if (param_matrixWorld.m11() > 1)
     {
-        if (param_matrixWorld.m11() >= threshold_zoom_img_region)
-        {
-            if (centralWidget->param_flags == CV_WINDOW_NORMAL)
-                startDisplayInfo("WARNING: The values displayed are the resized image's values. If you want the original image's values, use CV_WINDOW_AUTOSIZE", 1000);
-
-            drawImgRegion(&myPainter);
-        }
-
         drawViewOverview(&myPainter);
     }
 
@@ -2887,22 +2886,24 @@ void DefaultViewPort::drawStatusBar()
 //accept only CV_8UC1 and CV_8UC8 image for now
 void DefaultViewPort::drawImgRegion(QPainter *painter)
 {
-
     if (nbChannelOriginImage!=CV_8UC1 && nbChannelOriginImage!=CV_8UC3)
         return;
 
-    qreal offsetX = param_matrixWorld.dx()/param_matrixWorld.m11();
+    double pixel_width = param_matrixWorld.m11()*ratioX;
+    double pixel_height = param_matrixWorld.m11()*ratioY;
+
+    qreal offsetX = param_matrixWorld.dx()/pixel_width;
     offsetX = offsetX - floor(offsetX);
-    qreal offsetY = param_matrixWorld.dy()/param_matrixWorld.m11();
+    qreal offsetY = param_matrixWorld.dy()/pixel_height;
     offsetY = offsetY - floor(offsetY);
 
     QSize view = size();
     QVarLengthArray<QLineF, 30> linesX;
-    for (qreal _x = offsetX*param_matrixWorld.m11(); _x < view.width(); _x += param_matrixWorld.m11() )
+    for (qreal _x = offsetX*pixel_width; _x < view.width(); _x += pixel_width )
         linesX.append(QLineF(_x, 0, _x, view.height()));
 
     QVarLengthArray<QLineF, 30> linesY;
-    for (qreal _y = offsetY*param_matrixWorld.m11(); _y < view.height(); _y += param_matrixWorld.m11() )
+    for (qreal _y = offsetY*pixel_height; _y < view.height(); _y += pixel_height )
         linesY.append(QLineF(0, _y, view.width(), _y));
 
 
@@ -2910,27 +2911,25 @@ void DefaultViewPort::drawImgRegion(QPainter *painter)
     int original_font_size = f.pointSize();
     //change font size
     //f.setPointSize(4+(param_matrixWorld.m11()-threshold_zoom_img_region)/5);
-    f.setPixelSize(10+(param_matrixWorld.m11()-threshold_zoom_img_region)/5);
+    f.setPixelSize(10+(pixel_height-threshold_zoom_img_region)/5);
     painter->setFont(f);
-    QString val;
-    QRgb rgbValue;
 
-    QPointF point1;//sorry, I do not know how to name it
-    QPointF point2;//idem
 
-    for (int j=-1;j<height()/param_matrixWorld.m11();j++)//-1 because display the pixels top rows left colums
-        for (int i=-1;i<width()/param_matrixWorld.m11();i++)//-1
+    for (int j=-1;j<height()/pixel_height;j++)//-1 because display the pixels top rows left columns
+        for (int i=-1;i<width()/pixel_width;i++)//-1
         {
-            point1.setX((i+offsetX)*param_matrixWorld.m11());
-            point1.setY((j+offsetY)*param_matrixWorld.m11());
-
-            matrixWorld_inv.map(point1.x(),point1.y(),&point2.rx(),&point2.ry());
-
-            point2.rx()= (long) (point2.x() + 0.5);
-            point2.ry()= (long) (point2.y() + 0.5);
-
-            if (point2.x() >= 0 && point2.y() >= 0)
-                rgbValue = image2Draw_qt_resized.pixel(QPoint(point2.x(),point2.y()));
+            // Calculate top left of the pixel's position in the viewport (screen space)
+            QPointF pos_in_view((i+offsetX)*pixel_width, (j+offsetY)*pixel_height);
+
+            // Calculate top left of the pixel's position in the image (image space)
+            QPointF pos_in_image = matrixWorld_inv.map(pos_in_view);// Top left of pixel in view
+            pos_in_image.rx() = pos_in_image.x()/ratioX;
+            pos_in_image.ry() = pos_in_image.y()/ratioY;
+            QPoint point_in_image(pos_in_image.x() + 0.5f,pos_in_image.y() + 0.5f);// Add 0.5 for rounding
+
+            QRgb rgbValue;
+            if (image2Draw_qt.valid(point_in_image))
+                rgbValue = image2Draw_qt.pixel(point_in_image);
             else
                 rgbValue = qRgb(0,0,0);
 
@@ -2943,29 +2942,29 @@ void DefaultViewPort::drawImgRegion(QPainter *painter)
                 painter->drawText(QRect(point1.x(),point1.y(),param_matrixWorld.m11(),param_matrixWorld.m11()/2),
                     Qt::AlignCenter, val);
                 */
+                QString val;
 
                 val = tr("%1").arg(qRed(rgbValue));
                 painter->setPen(QPen(Qt::red, 1));
-                painter->drawText(QRect(point1.x(),point1.y(),param_matrixWorld.m11(),param_matrixWorld.m11()/3),
+                painter->drawText(QRect(pos_in_view.x(),pos_in_view.y(),pixel_width,pixel_height/3),
                     Qt::AlignCenter, val);
 
                 val = tr("%1").arg(qGreen(rgbValue));
                 painter->setPen(QPen(Qt::green, 1));
-                painter->drawText(QRect(point1.x(),point1.y()+param_matrixWorld.m11()/3,param_matrixWorld.m11(),param_matrixWorld.m11()/3),
+                painter->drawText(QRect(pos_in_view.x(),pos_in_view.y()+pixel_height/3,pixel_width,pixel_height/3),
                     Qt::AlignCenter, val);
 
                 val = tr("%1").arg(qBlue(rgbValue));
                 painter->setPen(QPen(Qt::blue, 1));
-                painter->drawText(QRect(point1.x(),point1.y()+2*param_matrixWorld.m11()/3,param_matrixWorld.m11(),param_matrixWorld.m11()/3),
+                painter->drawText(QRect(pos_in_view.x(),pos_in_view.y()+2*pixel_height/3,pixel_width,pixel_height/3),
                     Qt::AlignCenter, val);
 
             }
 
             if (nbChannelOriginImage==CV_8UC1)
             {
-
-                val = tr("%1").arg(qRed(rgbValue));
-                painter->drawText(QRect(point1.x(),point1.y(),param_matrixWorld.m11(),param_matrixWorld.m11()),
+                QString val = tr("%1").arg(qRed(rgbValue));
+                painter->drawText(QRect(pos_in_view.x(),pos_in_view.y(),pixel_width,pixel_height),
                     Qt::AlignCenter, val);
             }
         }

From 7d0f6b4d68b37234acdb0a399e2e95b9a7d39143 Mon Sep 17 00:00:00 2001
From: Leszek Swirski <leszek@swirski.co.uk>
Date: Tue, 21 May 2013 17:54:58 +0100
Subject: [PATCH 02/27] Fix image saving from QT toolbar

---
 modules/highgui/src/window_QT.cpp | 18 ++++++++----------
 modules/highgui/src/window_QT.h   |  1 -
 2 files changed, 8 insertions(+), 11 deletions(-)

diff --git a/modules/highgui/src/window_QT.cpp b/modules/highgui/src/window_QT.cpp
index 438c356f73..0c50c7070c 100644
--- a/modules/highgui/src/window_QT.cpp
+++ b/modules/highgui/src/window_QT.cpp
@@ -2473,35 +2473,33 @@ void DefaultViewPort::saveView()
     if (!fileName.isEmpty()) //save the picture
     {
         QString extension = fileName.right(3);
-
-        //   (no need anymore) create the image resized to receive the 'screenshot'
-        //    image2Draw_qt_resized = QImage(viewport()->width(), viewport()->height(),QImage::Format_RGB888);
-
-        QPainter saveimage(&image2Draw_qt_resized);
-        this->render(&saveimage);
+        
+        // Create a new pixmap to render the viewport into
+        QPixmap viewportPixmap(viewport()->size());
+        viewport()->render(&viewportPixmap);
 
         // Save it..
         if (QString::compare(extension, "png", Qt::CaseInsensitive) == 0)
         {
-            image2Draw_qt_resized.save(fileName, "PNG");
+            viewportPixmap.save(fileName, "PNG");
             return;
         }
 
         if (QString::compare(extension, "jpg", Qt::CaseInsensitive) == 0)
         {
-            image2Draw_qt_resized.save(fileName, "JPG");
+            viewportPixmap.save(fileName, "JPG");
             return;
         }
 
         if (QString::compare(extension, "bmp", Qt::CaseInsensitive) == 0)
         {
-            image2Draw_qt_resized.save(fileName, "BMP");
+            viewportPixmap.save(fileName, "BMP");
             return;
         }
 
         if (QString::compare(extension, "jpeg", Qt::CaseInsensitive) == 0)
         {
-            image2Draw_qt_resized.save(fileName, "JPEG");
+            viewportPixmap.save(fileName, "JPEG");
             return;
         }
 
diff --git a/modules/highgui/src/window_QT.h b/modules/highgui/src/window_QT.h
index 089997f514..a96a8c6e69 100644
--- a/modules/highgui/src/window_QT.h
+++ b/modules/highgui/src/window_QT.h
@@ -522,7 +522,6 @@ private:
 
     CvMat* image2Draw_mat;
     QImage image2Draw_qt;
-    QImage image2Draw_qt_resized;
     int nbChannelOriginImage;
 
     //for mouse callback

From 0cee15eb7f8e10361e008b0428f70e9a781a75d6 Mon Sep 17 00:00:00 2001
From: Alexander Shishkov <alexander.shishkov@itseez.com>
Date: Fri, 14 Jun 2013 15:10:25 +0400
Subject: [PATCH 03/27] Updated iOS camera. Added rotation flag. Added
 functions to lock/unlock focus, white balance and exposure.

---
 .../highgui/include/opencv2/highgui/cap_ios.h | 12 ++-
 .../highgui/src/cap_ios_abstract_camera.mm    | 85 +++++++++++++++++++
 modules/highgui/src/cap_ios_photo_camera.mm   |  2 +-
 modules/highgui/src/cap_ios_video_camera.mm   | 53 +++++++++---
 4 files changed, 138 insertions(+), 14 deletions(-)

diff --git a/modules/highgui/include/opencv2/highgui/cap_ios.h b/modules/highgui/include/opencv2/highgui/cap_ios.h
index 5bd5fe3c67..db3928f13b 100644
--- a/modules/highgui/include/opencv2/highgui/cap_ios.h
+++ b/modules/highgui/include/opencv2/highgui/cap_ios.h
@@ -1,6 +1,4 @@
-/*
- *  cap_ios.h
- *  For iOS video I/O
+/*  For iOS video I/O
  *  by Eduard Feicho on 29/07/12
  *  Copyright 2012. All rights reserved.
  *
@@ -90,6 +88,12 @@
 - (void)createVideoPreviewLayer;
 - (void)updateOrientation;
 
+- (void)lockFocus;
+- (void)unlockFocus;
+- (void)lockExposure;
+- (void)unlockExposure;
+- (void)lockBalance;
+- (void)unlockBalance;
 
 @end
 
@@ -116,6 +120,7 @@
     BOOL grayscaleMode;
 
     BOOL recordVideo;
+    BOOL rotateVideo;
     AVAssetWriterInput* recordAssetWriterInput;
     AVAssetWriterInputPixelBufferAdaptor* recordPixelBufferAdaptor;
     AVAssetWriter* recordAssetWriter;
@@ -128,6 +133,7 @@
 @property (nonatomic, assign) BOOL grayscaleMode;
 
 @property (nonatomic, assign) BOOL recordVideo;
+@property (nonatomic, assign) BOOL rotateVideo;
 @property (nonatomic, retain) AVAssetWriterInput* recordAssetWriterInput;
 @property (nonatomic, retain) AVAssetWriterInputPixelBufferAdaptor* recordPixelBufferAdaptor;
 @property (nonatomic, retain) AVAssetWriter* recordAssetWriter;
diff --git a/modules/highgui/src/cap_ios_abstract_camera.mm b/modules/highgui/src/cap_ios_abstract_camera.mm
index b6a7d944fa..a0e8f3e8b5 100644
--- a/modules/highgui/src/cap_ios_abstract_camera.mm
+++ b/modules/highgui/src/cap_ios_abstract_camera.mm
@@ -405,4 +405,89 @@
     }
 }
 
+- (void)lockFocus;
+{
+    AVCaptureDevice *device = [AVCaptureDevice defaultDeviceWithMediaType:AVMediaTypeVideo];
+    if ([device isFocusModeSupported:AVCaptureFocusModeLocked]) {
+        NSError *error = nil;
+        if ([device lockForConfiguration:&error]) {
+            device.focusMode = AVCaptureFocusModeLocked;
+            [device unlockForConfiguration];
+        } else {
+            NSLog(@"unable to lock device for locked focus configuration %@", [error localizedDescription]);
+        }
+    }
+}
+
+- (void) unlockFocus;
+{
+    AVCaptureDevice *device = [AVCaptureDevice defaultDeviceWithMediaType:AVMediaTypeVideo];
+    if ([device isFocusModeSupported:AVCaptureFocusModeContinuousAutoFocus]) {
+        NSError *error = nil;
+        if ([device lockForConfiguration:&error]) {
+            device.focusMode = AVCaptureFocusModeContinuousAutoFocus;
+            [device unlockForConfiguration];
+        } else {
+            NSLog(@"unable to lock device for autofocus configuration %@", [error localizedDescription]);
+        }
+    }
+}
+
+- (void)lockExposure;
+{
+    AVCaptureDevice *device = [AVCaptureDevice defaultDeviceWithMediaType:AVMediaTypeVideo];
+    if ([device isExposureModeSupported:AVCaptureExposureModeLocked]) {
+        NSError *error = nil;
+        if ([device lockForConfiguration:&error]) {
+            device.exposureMode = AVCaptureExposureModeLocked;
+            [device unlockForConfiguration];
+        } else {
+            NSLog(@"unable to lock device for locked exposure configuration %@", [error localizedDescription]);
+        }
+    }
+}
+
+- (void) unlockExposure;
+{
+    AVCaptureDevice *device = [AVCaptureDevice defaultDeviceWithMediaType:AVMediaTypeVideo];
+    if ([device isExposureModeSupported:AVCaptureExposureModeContinuousAutoExposure]) {
+        NSError *error = nil;
+        if ([device lockForConfiguration:&error]) {
+            device.exposureMode = AVCaptureExposureModeContinuousAutoExposure;
+            [device unlockForConfiguration];
+        } else {
+            NSLog(@"unable to lock device for autoexposure configuration %@", [error localizedDescription]);
+        }
+    }
+}
+
+- (void)lockBalance;
+{
+    AVCaptureDevice *device = [AVCaptureDevice defaultDeviceWithMediaType:AVMediaTypeVideo];
+    if ([device isWhiteBalanceModeSupported:AVCaptureWhiteBalanceModeLocked]) {
+        NSError *error = nil;
+        if ([device lockForConfiguration:&error]) {
+            device.whiteBalanceMode = AVCaptureWhiteBalanceModeLocked;
+            [device unlockForConfiguration];
+        } else {
+            NSLog(@"unable to lock device for locked exposure configuration %@", [error localizedDescription]);
+        }
+    }
+}
+
+- (void) unlockBalance;
+{
+    AVCaptureDevice *device = [AVCaptureDevice defaultDeviceWithMediaType:AVMediaTypeVideo];
+    if ([device isWhiteBalanceModeSupported:AVCaptureWhiteBalanceModeContinuousAutoWhiteBalance]) {
+        NSError *error = nil;
+        if ([device lockForConfiguration:&error]) {
+            device.whiteBalanceMode = AVCaptureWhiteBalanceModeContinuousAutoWhiteBalance;
+            [device unlockForConfiguration];
+        } else {
+            NSLog(@"unable to lock device for autoexposure configuration %@", [error localizedDescription]);
+        }
+    }
+}
+
 @end
+
diff --git a/modules/highgui/src/cap_ios_photo_camera.mm b/modules/highgui/src/cap_ios_photo_camera.mm
index f05cfa5f87..f8891f2277 100644
--- a/modules/highgui/src/cap_ios_photo_camera.mm
+++ b/modules/highgui/src/cap_ios_photo_camera.mm
@@ -32,7 +32,7 @@
 #import "opencv2/highgui/cap_ios.h"
 #include "precomp.hpp"
 
-#pragma mark - Private Interface
+#pragma mark - Private Interface mark - Private Interface
 
 
 @interface CvPhotoCamera ()
diff --git a/modules/highgui/src/cap_ios_video_camera.mm b/modules/highgui/src/cap_ios_video_camera.mm
index 1f9ea14bf8..588adfc9cc 100644
--- a/modules/highgui/src/cap_ios_video_camera.mm
+++ b/modules/highgui/src/cap_ios_video_camera.mm
@@ -30,7 +30,6 @@
 
 #import "opencv2/highgui/cap_ios.h"
 #include "precomp.hpp"
-
 #import <AssetsLibrary/AssetsLibrary.h>
 
 
@@ -70,6 +69,7 @@ static CGFloat DegreesToRadians(CGFloat degrees) {return degrees * M_PI / 180;};
 @synthesize videoDataOutput;
 
 @synthesize recordVideo;
+@synthesize rotateVideo;
 //@synthesize videoFileOutput;
 @synthesize recordAssetWriterInput;
 @synthesize recordPixelBufferAdaptor;
@@ -85,6 +85,7 @@ static CGFloat DegreesToRadians(CGFloat degrees) {return degrees * M_PI / 180;};
     if (self) {
         self.useAVCaptureVideoPreviewLayer = NO;
         self.recordVideo = NO;
+        self.rotateVideo = NO;
     }
     return self;
 }
@@ -269,13 +270,8 @@ static CGFloat DegreesToRadians(CGFloat degrees) {return degrees * M_PI / 180;};
 
 }
 
-
-
-
 #pragma mark - Private Interface
 
-
-
 - (void)createVideoDataOutput;
 {
     // Make a video data output
@@ -389,6 +385,38 @@ static CGFloat DegreesToRadians(CGFloat degrees) {return degrees * M_PI / 180;};
     [self.parentView.layer addSublayer:self.customPreviewLayer];
 }
 
+- (CVPixelBufferRef) pixelBufferFromCGImage: (CGImageRef) image
+{
+    
+    CGSize frameSize = CGSizeMake(CGImageGetWidth(image), CGImageGetHeight(image));
+    NSDictionary *options = [NSDictionary dictionaryWithObjectsAndKeys:
+                             [NSNumber numberWithBool:NO], kCVPixelBufferCGImageCompatibilityKey,
+                             [NSNumber numberWithBool:NO], kCVPixelBufferCGBitmapContextCompatibilityKey,
+                             nil];
+    CVPixelBufferRef pxbuffer = NULL;
+    CVReturn status = CVPixelBufferCreate(kCFAllocatorDefault, frameSize.width,
+                                          frameSize.height,  kCVPixelFormatType_32ARGB, (CFDictionaryRef) CFBridgingRetain(options),
+                                          &pxbuffer);
+    NSParameterAssert(status == kCVReturnSuccess && pxbuffer != NULL);
+    
+    CVPixelBufferLockBaseAddress(pxbuffer, 0);
+    void *pxdata = CVPixelBufferGetBaseAddress(pxbuffer);
+    
+    
+    CGColorSpaceRef rgbColorSpace = CGColorSpaceCreateDeviceRGB();
+    CGContextRef context = CGBitmapContextCreate(pxdata, frameSize.width,
+                                                 frameSize.height, 8, 4*frameSize.width, rgbColorSpace,
+                                                 kCGImageAlphaPremultipliedFirst);
+    
+    CGContextDrawImage(context, CGRectMake(0, 0, CGImageGetWidth(image),
+                                           CGImageGetHeight(image)), image);
+    CGColorSpaceRelease(rgbColorSpace);
+    CGContextRelease(context);
+    
+    CVPixelBufferUnlockBaseAddress(pxbuffer, 0);
+    
+    return pxbuffer;
+}
 
 #pragma mark - Protocol AVCaptureVideoDataOutputSampleBufferDelegate
 
@@ -522,7 +550,8 @@ static CGFloat DegreesToRadians(CGFloat degrees) {return degrees * M_PI / 180;};
             }
 
             if (self.recordAssetWriterInput.readyForMoreMediaData) {
-                if (! [self.recordPixelBufferAdaptor appendPixelBuffer:imageBuffer
+                CVImageBufferRef pixelBuffer = [self pixelBufferFromCGImage:dstImage];
+                if (! [self.recordPixelBufferAdaptor appendPixelBuffer:pixelBuffer
                                                   withPresentationTime:lastSampleTime] ) {
                     NSLog(@"Video Writing Error");
                 }
@@ -543,9 +572,12 @@ static CGFloat DegreesToRadians(CGFloat degrees) {return degrees * M_PI / 180;};
 
 - (void)updateOrientation;
 {
-    NSLog(@"rotate..");
-    self.customPreviewLayer.bounds = CGRectMake(0, 0, self.parentView.frame.size.width, self.parentView.frame.size.height);
-    [self layoutPreviewLayer];
+    if (self.rotateVideo == YES)
+    {
+        NSLog(@"rotate..");
+        self.customPreviewLayer.bounds = CGRectMake(0, 0, self.parentView.frame.size.width, self.parentView.frame.size.height);
+        [self layoutPreviewLayer];
+    }
 }
 
 
@@ -583,3 +615,4 @@ static CGFloat DegreesToRadians(CGFloat degrees) {return degrees * M_PI / 180;};
 }
 
 @end
+

From fee81210405ce01bccc810be59c957b8f9d227dc Mon Sep 17 00:00:00 2001
From: Ivan Korolev <ivan.korolev@itseez.com>
Date: Fri, 14 Jun 2013 17:03:15 +0400
Subject: [PATCH 04/27] Added regression tests for SURF/SIFT (related to #2892)

---
 modules/nonfree/test/test_features2d.cpp | 73 ++++++++++++++++++++++++
 1 file changed, 73 insertions(+)

diff --git a/modules/nonfree/test/test_features2d.cpp b/modules/nonfree/test/test_features2d.cpp
index 001d628aaa..4cce77b9d5 100644
--- a/modules/nonfree/test/test_features2d.cpp
+++ b/modules/nonfree/test/test_features2d.cpp
@@ -1146,3 +1146,76 @@ protected:
 TEST(Features2d_SIFTHomographyTest, regression) { CV_DetectPlanarTest test("SIFT", 80); test.safe_run(); }
 TEST(Features2d_SURFHomographyTest, regression) { CV_DetectPlanarTest test("SURF", 80); test.safe_run(); }
 
+class FeatureDetectorUsingMaskTest : public cvtest::BaseTest
+{
+public:
+    FeatureDetectorUsingMaskTest(const Ptr<FeatureDetector>& featureDetector) :
+        featureDetector_(featureDetector)
+    {
+        CV_Assert(!featureDetector_.empty());
+    }
+
+protected:
+
+    void run(int)
+    {
+        const int nStepX = 2;
+        const int nStepY = 2;
+
+        const string imageFilename = string(ts->get_data_path()) + "/features2d/tsukuba.png";
+
+        Mat image = imread(imageFilename);
+        if(image.empty())
+        {
+            ts->printf(cvtest::TS::LOG, "Image %s can not be read.\n", imageFilename.c_str());
+            ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
+            return;
+        }
+
+        Mat mask(image.size(), CV_8U);
+
+        const int stepX = image.size().width / nStepX;
+        const int stepY = image.size().height / nStepY;
+
+        vector<KeyPoint> keyPoints;
+        vector<Point2f> points;
+        for(int i=0; i<nStepX; ++i)
+            for(int j=0; j<nStepY; ++j)
+            {
+
+                mask.setTo(0);
+                Rect whiteArea(i * stepX, j * stepY, stepX, stepY);
+                mask(whiteArea).setTo(255);
+
+                featureDetector_->detect(image, keyPoints, mask);
+                KeyPoint::convert(keyPoints, points);
+
+                for(size_t k=0; k<points.size(); ++k)
+                {
+                    if ( !whiteArea.contains(points[k]) )
+                    {
+                        ts->printf(cvtest::TS::LOG, "The feature point is outside of the mask.");
+                        ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
+                        return;
+                    }
+                }
+            }
+
+        ts->set_failed_test_info( cvtest::TS::OK );
+    }
+
+    Ptr<FeatureDetector> featureDetector_;
+};
+
+TEST(Features2d_SIFT_using_mask, regression)
+{
+    FeatureDetectorUsingMaskTest test(Algorithm::create<FeatureDetector>("Feature2D.SIFT"));
+    test.safe_run();
+}
+
+TEST(DISABLED_Features2d_SURF_using_mask, regression)
+{
+    FeatureDetectorUsingMaskTest test(Algorithm::create<FeatureDetector>("Feature2D.SURF"));
+    test.safe_run();
+}
+

From 5db08961cec08f309c3165fa086a0eb8e8e5d6ee Mon Sep 17 00:00:00 2001
From: Alexander Shishkov <alexander.shishkov@itseez.com>
Date: Tue, 18 Jun 2013 06:59:52 +0400
Subject: [PATCH 05/27] fixed Kirill's comments

---
 modules/highgui/src/cap_ios_abstract_camera.mm | 4 ++--
 modules/highgui/src/cap_ios_photo_camera.mm    | 2 +-
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/modules/highgui/src/cap_ios_abstract_camera.mm b/modules/highgui/src/cap_ios_abstract_camera.mm
index a0e8f3e8b5..dc4faaaeff 100644
--- a/modules/highgui/src/cap_ios_abstract_camera.mm
+++ b/modules/highgui/src/cap_ios_abstract_camera.mm
@@ -470,7 +470,7 @@
             device.whiteBalanceMode = AVCaptureWhiteBalanceModeLocked;
             [device unlockForConfiguration];
         } else {
-            NSLog(@"unable to lock device for locked exposure configuration %@", [error localizedDescription]);
+            NSLog(@"unable to lock device for locked white balance configuration %@", [error localizedDescription]);
         }
     }
 }
@@ -484,7 +484,7 @@
             device.whiteBalanceMode = AVCaptureWhiteBalanceModeContinuousAutoWhiteBalance;
             [device unlockForConfiguration];
         } else {
-            NSLog(@"unable to lock device for autoexposure configuration %@", [error localizedDescription]);
+            NSLog(@"unable to lock device for auto white balance configuration %@", [error localizedDescription]);
         }
     }
 }
diff --git a/modules/highgui/src/cap_ios_photo_camera.mm b/modules/highgui/src/cap_ios_photo_camera.mm
index f8891f2277..f05cfa5f87 100644
--- a/modules/highgui/src/cap_ios_photo_camera.mm
+++ b/modules/highgui/src/cap_ios_photo_camera.mm
@@ -32,7 +32,7 @@
 #import "opencv2/highgui/cap_ios.h"
 #include "precomp.hpp"
 
-#pragma mark - Private Interface mark - Private Interface
+#pragma mark - Private Interface
 
 
 @interface CvPhotoCamera ()

From 24fd2cc326db17a511eda02670dd64209b7b689a Mon Sep 17 00:00:00 2001
From: Alexander Shishkov <alexander.shishkov@itseez.com>
Date: Tue, 18 Jun 2013 07:02:09 +0400
Subject: [PATCH 06/27] updated licenses

---
 modules/highgui/src/cap_ios_abstract_camera.mm | 1 +
 modules/highgui/src/cap_ios_video_camera.mm    | 1 +
 2 files changed, 2 insertions(+)

diff --git a/modules/highgui/src/cap_ios_abstract_camera.mm b/modules/highgui/src/cap_ios_abstract_camera.mm
index dc4faaaeff..38e1c12e68 100644
--- a/modules/highgui/src/cap_ios_abstract_camera.mm
+++ b/modules/highgui/src/cap_ios_abstract_camera.mm
@@ -2,6 +2,7 @@
  *  cap_ios_abstract_camera.mm
  *  For iOS video I/O
  *  by Eduard Feicho on 29/07/12
+ *  by Alexander Shishkov on 17/07/13
  *  Copyright 2012. All rights reserved.
  *
  * Redistribution and use in source and binary forms, with or without
diff --git a/modules/highgui/src/cap_ios_video_camera.mm b/modules/highgui/src/cap_ios_video_camera.mm
index 588adfc9cc..ac85f79ee5 100644
--- a/modules/highgui/src/cap_ios_video_camera.mm
+++ b/modules/highgui/src/cap_ios_video_camera.mm
@@ -2,6 +2,7 @@
  *  cap_ios_video_camera.mm
  *  For iOS video I/O
  *  by Eduard Feicho on 29/07/12
+ *  by Alexander Shishkov on 17/07/13
  *  Copyright 2012. All rights reserved.
  *
  * Redistribution and use in source and binary forms, with or without

From f003e29dc0e10fa7d28dd5c717fbec134b2bf67e Mon Sep 17 00:00:00 2001
From: Roman Donchenko <roman.donchenko@itseez.com>
Date: Thu, 13 Jun 2013 12:22:12 +0400
Subject: [PATCH 07/27] Updated testlog_parser.py to the latest version from
 the private repo.

---
 modules/ts/misc/testlog_parser.py | 39 +++++++++++++++++--------------
 1 file changed, 22 insertions(+), 17 deletions(-)

diff --git a/modules/ts/misc/testlog_parser.py b/modules/ts/misc/testlog_parser.py
index 7ae6aa5980..8ab21417ca 100755
--- a/modules/ts/misc/testlog_parser.py
+++ b/modules/ts/misc/testlog_parser.py
@@ -100,34 +100,39 @@ class TestInfo(object):
     def dump(self, units="ms"):
         print "%s ->\t\033[1;31m%s\033[0m = \t%.2f%s" % (str(self), self.status, self.get("gmean", units), units)
 
-    def shortName(self):
+
+    def getName(self):
         pos = self.name.find("/")
         if pos > 0:
-            name = self.name[:pos]
-        else:
-            name = self.name
-        if self.fixture.endswith(name):
-            fixture = self.fixture[:-len(name)]
+            return self.name[:pos]
+        return self.name
+
+
+    def getFixture(self):
+        if self.fixture.endswith(self.getName()):
+            fixture = self.fixture[:-len(self.getName())]
         else:
             fixture = self.fixture
         if fixture.endswith("_"):
             fixture = fixture[:-1]
+        return fixture
+
+
+    def param(self):
+        return '::'.join(filter(None, [self.type_param, self.value_param]))
+
+    def shortName(self):
+        name = self.getName()
+        fixture = self.getFixture()
         return '::'.join(filter(None, [name, fixture]))
 
+
     def __str__(self):
-        pos = self.name.find("/")
-        if pos > 0:
-            name = self.name[:pos]
-        else:
-            name = self.name
-        if self.fixture.endswith(name):
-            fixture = self.fixture[:-len(name)]
-        else:
-            fixture = self.fixture
-        if fixture.endswith("_"):
-            fixture = fixture[:-1]
+        name = self.getName()
+        fixture = self.getFixture()
         return '::'.join(filter(None, [name, fixture, self.type_param, self.value_param]))
 
+
     def __cmp__(self, other):
         r = cmp(self.fixture, other.fixture);
         if r != 0:

From 6ff207b53a6379933018c88167ee11b5b1a62e2d Mon Sep 17 00:00:00 2001
From: Roman Donchenko <roman.donchenko@itseez.com>
Date: Fri, 14 Jun 2013 14:53:02 +0400
Subject: [PATCH 08/27] Added a new and improved version of the XLS report
 generator.

---
 modules/ts/misc/xls-report.py | 171 ++++++++++++++++++++++++++++++++++
 1 file changed, 171 insertions(+)
 create mode 100755 modules/ts/misc/xls-report.py

diff --git a/modules/ts/misc/xls-report.py b/modules/ts/misc/xls-report.py
new file mode 100755
index 0000000000..fb6cfd0960
--- /dev/null
+++ b/modules/ts/misc/xls-report.py
@@ -0,0 +1,171 @@
+#!/usr/bin/env python
+
+from __future__ import division
+
+import ast
+import logging
+import os, os.path
+import re
+
+from argparse import ArgumentParser
+from glob import glob
+from itertools import ifilter
+
+import xlwt
+
+from testlog_parser import parseLogFile
+
+# To build XLS report you neet to put your xmls (OpenCV tests output) in the
+# following way:
+#
+# "root" --- folder, representing the whole XLS document. It contains several
+# subfolders --- sheet-paths of the XLS document. Each sheet-path contains it's
+# subfolders --- config-paths. Config-paths are columns of the sheet and
+# they contains xmls files --- output of OpenCV modules testing.
+# Config-path means OpenCV build configuration, including different
+# options such as NEON, TBB, GPU enabling/disabling.
+#
+# root
+# root\sheet_path
+# root\sheet_path\configuration1 (column 1)
+# root\sheet_path\configuration2 (column 2)
+
+re_image_size = re.compile(r'^ \d+ x \d+$', re.VERBOSE)
+re_data_type = re.compile(r'^ (?: 8 | 16 | 32 | 64 ) [USF] C [1234] $', re.VERBOSE)
+
+time_style = xlwt.easyxf(num_format_str='#0.00')
+no_time_style = xlwt.easyxf('pattern: pattern solid, fore_color gray25')
+
+speedup_style = time_style
+good_speedup_style = xlwt.easyxf('font: color green', num_format_str='#0.00')
+bad_speedup_style = xlwt.easyxf('font: color red', num_format_str='#0.00')
+no_speedup_style = no_time_style
+error_speedup_style = xlwt.easyxf('pattern: pattern solid, fore_color orange')
+header_style = xlwt.easyxf('font: bold true; alignment: horizontal centre, vertical top')
+
+def collect_xml(collection, configuration, xml_fullname):
+    xml_fname = os.path.split(xml_fullname)[1]
+    module = xml_fname[:xml_fname.index('_')]
+
+    if module not in collection:
+        collection[module] = {}
+
+    for test in sorted(parseLogFile(xml_fullname)):
+        if test.shortName() not in collection[module]:
+            collection[module][test.shortName()] = {}
+        if test.param() not in collection[module][test.shortName()]:
+            collection[module][test.shortName()][test.param()] = {}
+        collection[module][test.shortName()][test.param()][configuration] = \
+            test.get("gmean")
+
+def main():
+    arg_parser = ArgumentParser(description='Build an XLS performance report.')
+    arg_parser.add_argument('sheet_dirs', nargs='+', metavar='DIR', help='directory containing perf test logs')
+    arg_parser.add_argument('-o', '--output', metavar='XLS', default='report.xls', help='name of output file')
+    arg_parser.add_argument('-c', '--config', metavar='CONF', help='global configuration file')
+
+    args = arg_parser.parse_args()
+
+    logging.basicConfig(format='%(levelname)s: %(message)s', level=logging.DEBUG)
+
+    if args.config is not None:
+        with open(args.config) as global_conf_file:
+            global_conf = ast.literal_eval(global_conf_file.read())
+    else:
+        global_conf = {}
+
+    wb = xlwt.Workbook()
+
+    for sheet_path in args.sheet_dirs:
+        try:
+            with open(os.path.join(sheet_path, 'sheet.conf')) as sheet_conf_file:
+                sheet_conf = ast.literal_eval(sheet_conf_file.read())
+        except Exception:
+            sheet_conf = {}
+            logging.debug('no sheet.conf for {}'.format(sheet_path))
+
+        sheet_conf = dict(global_conf.items() + sheet_conf.items())
+
+        if 'configurations' in sheet_conf:
+            config_names = sheet_conf['configurations']
+        else:
+            try:
+                config_names = [p for p in os.listdir(sheet_path)
+                    if os.path.isdir(os.path.join(sheet_path, p))]
+            except Exception as e:
+                logging.warning(e)
+                continue
+
+        collection = {}
+
+        for configuration, configuration_path in \
+                [(c, os.path.join(sheet_path, c))  for c in config_names]:
+            logging.info('processing {}'.format(configuration_path))
+            for xml_fullname in glob(os.path.join(configuration_path, '*.xml')):
+                collect_xml(collection, configuration, xml_fullname)
+
+        sheet = wb.add_sheet(sheet_conf.get('sheet_name', os.path.basename(os.path.abspath(sheet_path))))
+
+        sheet.row(0).height = 800
+        sheet.panes_frozen = True
+        sheet.remove_splits = True
+        sheet.horz_split_pos = 1
+        sheet.horz_split_first_visible = 1
+
+        sheet_comparisons = sheet_conf.get('comparisons', [])
+
+        for i, w in enumerate([2000, 15000, 2500, 2000, 15000]
+                + (len(config_names) + 1 + len(sheet_comparisons)) * [3000]):
+            sheet.col(i).width = w
+
+        for i, caption in enumerate(['Module', 'Test', 'Image\nsize', 'Data\ntype', 'Parameters']
+                + config_names + [None]
+                + [comp['from'] + '\nvs\n' + comp['to'] for comp in sheet_comparisons]):
+            sheet.row(0).write(i, caption, header_style)
+
+        row = 1
+
+        module_colors = sheet_conf.get('module_colors', {})
+        module_styles = {module: xlwt.easyxf('pattern: pattern solid, fore_color {}'.format(color))
+                         for module, color in module_colors.iteritems()}
+
+        for module, tests in collection.iteritems():
+            for test, params in tests.iteritems():
+                for param, configs in params.iteritems():
+                    sheet.write(row, 0, module, module_styles.get(module, xlwt.Style.default_style))
+                    sheet.write(row, 1, test)
+
+                    param_list = param[1:-1].split(", ")
+                    sheet.write(row, 2, next(ifilter(re_image_size.match, param_list), None))
+                    sheet.write(row, 3, next(ifilter(re_data_type.match, param_list), None))
+
+                    sheet.row(row).write(4, param)
+                    for i, c in enumerate(config_names):
+                        if c in configs:
+                            sheet.write(row, 5 + i, configs[c], time_style)
+                        else:
+                            sheet.write(row, 5 + i, None, no_time_style)
+
+                    for i, comp in enumerate(sheet_comparisons):
+                        left = configs.get(comp["from"])
+                        right = configs.get(comp["to"])
+                        col = 5 + len(config_names) + 1 + i
+
+                        if left is not None and right is not None:
+                            try:
+                                speedup = left / right
+                                sheet.write(row, col, speedup, good_speedup_style if speedup > 1.1 else
+                                                               bad_speedup_style  if speedup < 0.9 else
+                                                               speedup_style)
+                            except ArithmeticError as e:
+                                sheet.write(row, col, None, error_speedup_style)
+                        else:
+                            sheet.write(row, col, None, no_speedup_style)
+
+                    row += 1
+                    if row % 1000 == 0: sheet.flush_row_data()
+
+    wb.save(args.output)
+
+if __name__ == '__main__':
+    main()

From 4d7b1b5eded9cfbb456b0238a2f55c6f6ae491ee Mon Sep 17 00:00:00 2001
From: Roman Donchenko <roman.donchenko@itseez.com>
Date: Mon, 17 Jun 2013 21:06:02 +0400
Subject: [PATCH 09/27] In the XLS report, enabled word wrapping for header
 cells.

Otherwise, Excel ignores line breaks in them.
---
 modules/ts/misc/xls-report.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/ts/misc/xls-report.py b/modules/ts/misc/xls-report.py
index fb6cfd0960..f8288e16da 100755
--- a/modules/ts/misc/xls-report.py
+++ b/modules/ts/misc/xls-report.py
@@ -41,7 +41,7 @@ good_speedup_style = xlwt.easyxf('font: color green', num_format_str='#0.00')
 bad_speedup_style = xlwt.easyxf('font: color red', num_format_str='#0.00')
 no_speedup_style = no_time_style
 error_speedup_style = xlwt.easyxf('pattern: pattern solid, fore_color orange')
-header_style = xlwt.easyxf('font: bold true; alignment: horizontal centre, vertical top')
+header_style = xlwt.easyxf('font: bold true; alignment: horizontal centre, vertical top, wrap True')
 
 def collect_xml(collection, configuration, xml_fullname):
     xml_fname = os.path.split(xml_fullname)[1]

From 0f1156bbb61efa0ec7d7b48e8a0cd02ec72378ba Mon Sep 17 00:00:00 2001
From: Roman Donchenko <roman.donchenko@itseez.com>
Date: Tue, 18 Jun 2013 13:36:20 +0400
Subject: [PATCH 10/27] Made the order of tests in XLS reports deterministic.

---
 modules/ts/misc/xls-report.py | 81 ++++++++++++++++-------------------
 1 file changed, 38 insertions(+), 43 deletions(-)

diff --git a/modules/ts/misc/xls-report.py b/modules/ts/misc/xls-report.py
index f8288e16da..7e63b6737c 100755
--- a/modules/ts/misc/xls-report.py
+++ b/modules/ts/misc/xls-report.py
@@ -8,6 +8,7 @@ import os, os.path
 import re
 
 from argparse import ArgumentParser
+from collections import OrderedDict
 from glob import glob
 from itertools import ifilter
 
@@ -47,16 +48,11 @@ def collect_xml(collection, configuration, xml_fullname):
     xml_fname = os.path.split(xml_fullname)[1]
     module = xml_fname[:xml_fname.index('_')]
 
-    if module not in collection:
-        collection[module] = {}
+    module_tests = collection.setdefault(module, OrderedDict())
 
     for test in sorted(parseLogFile(xml_fullname)):
-        if test.shortName() not in collection[module]:
-            collection[module][test.shortName()] = {}
-        if test.param() not in collection[module][test.shortName()]:
-            collection[module][test.shortName()][test.param()] = {}
-        collection[module][test.shortName()][test.param()][configuration] = \
-            test.get("gmean")
+        test_results = module_tests.setdefault((test.shortName(), test.param()), {})
+        test_results[configuration] = test.get("gmean")
 
 def main():
     arg_parser = ArgumentParser(description='Build an XLS performance report.')
@@ -129,41 +125,40 @@ def main():
         module_styles = {module: xlwt.easyxf('pattern: pattern solid, fore_color {}'.format(color))
                          for module, color in module_colors.iteritems()}
 
-        for module, tests in collection.iteritems():
-            for test, params in tests.iteritems():
-                for param, configs in params.iteritems():
-                    sheet.write(row, 0, module, module_styles.get(module, xlwt.Style.default_style))
-                    sheet.write(row, 1, test)
-
-                    param_list = param[1:-1].split(", ")
-                    sheet.write(row, 2, next(ifilter(re_image_size.match, param_list), None))
-                    sheet.write(row, 3, next(ifilter(re_data_type.match, param_list), None))
-
-                    sheet.row(row).write(4, param)
-                    for i, c in enumerate(config_names):
-                        if c in configs:
-                            sheet.write(row, 5 + i, configs[c], time_style)
-                        else:
-                            sheet.write(row, 5 + i, None, no_time_style)
-
-                    for i, comp in enumerate(sheet_comparisons):
-                        left = configs.get(comp["from"])
-                        right = configs.get(comp["to"])
-                        col = 5 + len(config_names) + 1 + i
-
-                        if left is not None and right is not None:
-                            try:
-                                speedup = left / right
-                                sheet.write(row, col, speedup, good_speedup_style if speedup > 1.1 else
-                                                               bad_speedup_style  if speedup < 0.9 else
-                                                               speedup_style)
-                            except ArithmeticError as e:
-                                sheet.write(row, col, None, error_speedup_style)
-                        else:
-                            sheet.write(row, col, None, no_speedup_style)
-
-                    row += 1
-                    if row % 1000 == 0: sheet.flush_row_data()
+        for module, tests in sorted(collection.iteritems()):
+            for ((test, param), configs) in tests.iteritems():
+                sheet.write(row, 0, module, module_styles.get(module, xlwt.Style.default_style))
+                sheet.write(row, 1, test)
+
+                param_list = param[1:-1].split(", ")
+                sheet.write(row, 2, next(ifilter(re_image_size.match, param_list), None))
+                sheet.write(row, 3, next(ifilter(re_data_type.match, param_list), None))
+
+                sheet.row(row).write(4, param)
+                for i, c in enumerate(config_names):
+                    if c in configs:
+                        sheet.write(row, 5 + i, configs[c], time_style)
+                    else:
+                        sheet.write(row, 5 + i, None, no_time_style)
+
+                for i, comp in enumerate(sheet_comparisons):
+                    left = configs.get(comp["from"])
+                    right = configs.get(comp["to"])
+                    col = 5 + len(config_names) + 1 + i
+
+                    if left is not None and right is not None:
+                        try:
+                            speedup = left / right
+                            sheet.write(row, col, speedup, good_speedup_style if speedup > 1.1 else
+                                                           bad_speedup_style  if speedup < 0.9 else
+                                                           speedup_style)
+                        except ArithmeticError as e:
+                            sheet.write(row, col, None, error_speedup_style)
+                    else:
+                        sheet.write(row, col, None, no_speedup_style)
+
+                row += 1
+                if row % 1000 == 0: sheet.flush_row_data()
 
     wb.save(args.output)
 

From 584f0745d0f917c993629c6e77bf898c6d243bf0 Mon Sep 17 00:00:00 2001
From: Roman Donchenko <roman.donchenko@itseez.com>
Date: Tue, 18 Jun 2013 12:30:05 +0400
Subject: [PATCH 11/27] Made xls-report.py ignore tests that were not
 successful.

---
 modules/ts/misc/xls-report.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/modules/ts/misc/xls-report.py b/modules/ts/misc/xls-report.py
index 7e63b6737c..f6278bae00 100755
--- a/modules/ts/misc/xls-report.py
+++ b/modules/ts/misc/xls-report.py
@@ -52,7 +52,8 @@ def collect_xml(collection, configuration, xml_fullname):
 
     for test in sorted(parseLogFile(xml_fullname)):
         test_results = module_tests.setdefault((test.shortName(), test.param()), {})
-        test_results[configuration] = test.get("gmean")
+        if test.status == 'run':
+            test_results[configuration] = test.get("gmean")
 
 def main():
     arg_parser = ArgumentParser(description='Build an XLS performance report.')

From 16c4aad36de4e42624e70baf677dc67d0c17fefa Mon Sep 17 00:00:00 2001
From: Alexander Smorkalov <alexander.smorkalov@itseez.com>
Date: Thu, 13 Jun 2013 15:38:21 +0400
Subject: [PATCH 12/27] Java/Python bindings for computeCorrespondEpilines
 added.

Simle Java test for computeCorrespondEpilines added.
---
 .../calib3d/include/opencv2/calib3d/calib3d.hpp    |  6 +++---
 .../src/org/opencv/test/calib3d/Calib3dTest.java   | 14 ++++++++++++++
 2 files changed, 17 insertions(+), 3 deletions(-)

diff --git a/modules/calib3d/include/opencv2/calib3d/calib3d.hpp b/modules/calib3d/include/opencv2/calib3d/calib3d.hpp
index 0d1cc46915..f213a114f4 100644
--- a/modules/calib3d/include/opencv2/calib3d/calib3d.hpp
+++ b/modules/calib3d/include/opencv2/calib3d/calib3d.hpp
@@ -639,9 +639,9 @@ CV_EXPORTS Mat findFundamentalMat( InputArray points1, InputArray points2,
                                    double param1=3., double param2=0.99);
 
 //! finds coordinates of epipolar lines corresponding the specified points
-CV_EXPORTS void computeCorrespondEpilines( InputArray points,
-                                           int whichImage, InputArray F,
-                                           OutputArray lines );
+CV_EXPORTS_W void computeCorrespondEpilines( InputArray points,
+                                             int whichImage, InputArray F,
+                                             OutputArray lines );
 
 CV_EXPORTS_W void triangulatePoints( InputArray projMatr1, InputArray projMatr2,
                                      InputArray projPoints1, InputArray projPoints2,
diff --git a/modules/java/android_test/src/org/opencv/test/calib3d/Calib3dTest.java b/modules/java/android_test/src/org/opencv/test/calib3d/Calib3dTest.java
index 8bcaf58a05..db806b6fc9 100644
--- a/modules/java/android_test/src/org/opencv/test/calib3d/Calib3dTest.java
+++ b/modules/java/android_test/src/org/opencv/test/calib3d/Calib3dTest.java
@@ -585,4 +585,18 @@ public class Calib3dTest extends OpenCVTestCase {
     public void testValidateDisparityMatMatIntIntInt() {
         fail("Not yet implemented");
     }
+
+    public void testComputeCorrespondEpilines()
+    {
+        Mat fundamental = new Mat(3, 3, CvType.CV_64F);
+        fundamental.put(0, 0, 0, -0.577, 0.288, 0.577, 0, 0.288, -0.288, -0.288, 0);
+        MatOfPoint2f left = new MatOfPoint2f();
+        left.alloc(1);
+        left.put(0, 0, 2, 3); //add(new Point(x, y));
+        Mat lines = new Mat();
+        Mat truth = new Mat(1, 1, CvType.CV_32FC3);
+        truth.put(0, 0, -0.70735186, 0.70686162, -0.70588124);
+        Calib3d.computeCorrespondEpilines(left, 1, fundamental, lines);
+        assertMatEqual(truth, lines, EPS);
+    }
 }

From 1492b204727066daae2967f1bb2831acde42eb92 Mon Sep 17 00:00:00 2001
From: Vladislav Vinogradov <vlad.vinogradov@itseez.com>
Date: Tue, 18 Jun 2013 13:17:33 +0400
Subject: [PATCH 13/27] fix gpu warnings with signed/unsigned char

---
 .../gpu/include/opencv2/gpu/device/limits.hpp | 231 +++++-------------
 modules/gpu/src/nvidia/core/NCV.hpp           |   2 +-
 .../src/nvidia/core/NCVPixelOperations.hpp    |   4 +-
 3 files changed, 62 insertions(+), 175 deletions(-)

diff --git a/modules/gpu/include/opencv2/gpu/device/limits.hpp b/modules/gpu/include/opencv2/gpu/device/limits.hpp
index b040f199d6..595978006c 100644
--- a/modules/gpu/include/opencv2/gpu/device/limits.hpp
+++ b/modules/gpu/include/opencv2/gpu/device/limits.hpp
@@ -43,193 +43,80 @@
 #ifndef __OPENCV_GPU_LIMITS_GPU_HPP__
 #define __OPENCV_GPU_LIMITS_GPU_HPP__
 
-#include <limits>
+#include <limits.h>
+#include <float.h>
 #include "common.hpp"
 
 namespace cv { namespace gpu { namespace device
 {
-    template<class T> struct numeric_limits
-    {
-        typedef T type;
-        __device__ __forceinline__ static type min()  { return type(); };
-        __device__ __forceinline__ static type max() { return type(); };
-        __device__ __forceinline__ static type epsilon() { return type(); }
-        __device__ __forceinline__ static type round_error() { return type(); }
-        __device__ __forceinline__ static type denorm_min()  { return type(); }
-        __device__ __forceinline__ static type infinity() { return type(); }
-        __device__ __forceinline__ static type quiet_NaN() { return type(); }
-        __device__ __forceinline__ static type signaling_NaN() { return T(); }
-        static const bool is_signed;
-    };
 
-    template<> struct numeric_limits<bool>
-    {
-        typedef bool type;
-        __device__ __forceinline__ static type min() { return false; };
-        __device__ __forceinline__ static type max() { return true;  };
-        __device__ __forceinline__ static type epsilon();
-        __device__ __forceinline__ static type round_error();
-        __device__ __forceinline__ static type denorm_min();
-        __device__ __forceinline__ static type infinity();
-        __device__ __forceinline__ static type quiet_NaN();
-        __device__ __forceinline__ static type signaling_NaN();
-        static const bool is_signed = false;
-    };
+template <class T> struct numeric_limits;
 
-    template<> struct numeric_limits<char>
-    {
-        typedef char type;
-        __device__ __forceinline__ static type min() { return CHAR_MIN; };
-        __device__ __forceinline__ static type max() { return CHAR_MAX; };
-        __device__ __forceinline__ static type epsilon();
-        __device__ __forceinline__ static type round_error();
-        __device__ __forceinline__ static type denorm_min();
-        __device__ __forceinline__ static type infinity();
-        __device__ __forceinline__ static type quiet_NaN();
-        __device__ __forceinline__ static type signaling_NaN();
-        static const bool is_signed = (char)-1 == -1;
-    };
-
-    template<> struct numeric_limits<signed char>
-    {
-        typedef char type;
-        __device__ __forceinline__ static type min() { return SCHAR_MIN; };
-        __device__ __forceinline__ static type max() { return SCHAR_MAX; };
-        __device__ __forceinline__ static type epsilon();
-        __device__ __forceinline__ static type round_error();
-        __device__ __forceinline__ static type denorm_min();
-        __device__ __forceinline__ static type infinity();
-        __device__ __forceinline__ static type quiet_NaN();
-        __device__ __forceinline__ static type signaling_NaN();
-        static const bool is_signed = (signed char)-1 == -1;
-    };
-
-    template<> struct numeric_limits<unsigned char>
-    {
-        typedef unsigned char type;
-        __device__ __forceinline__ static type min() { return 0; };
-        __device__ __forceinline__ static type max() { return UCHAR_MAX; };
-        __device__ __forceinline__ static type epsilon();
-        __device__ __forceinline__ static type round_error();
-        __device__ __forceinline__ static type denorm_min();
-        __device__ __forceinline__ static type infinity();
-        __device__ __forceinline__ static type quiet_NaN();
-        __device__ __forceinline__ static type signaling_NaN();
-        static const bool is_signed = false;
-    };
+template <> struct numeric_limits<bool>
+{
+    __device__ __forceinline__ static bool min() { return false; }
+    __device__ __forceinline__ static bool max() { return true;  }
+    static const bool is_signed = false;
+};
 
-    template<> struct numeric_limits<short>
-    {
-        typedef short type;
-        __device__ __forceinline__ static type min() { return SHRT_MIN; };
-        __device__ __forceinline__ static type max() { return SHRT_MAX; };
-        __device__ __forceinline__ static type epsilon();
-        __device__ __forceinline__ static type round_error();
-        __device__ __forceinline__ static type denorm_min();
-        __device__ __forceinline__ static type infinity();
-        __device__ __forceinline__ static type quiet_NaN();
-        __device__ __forceinline__ static type signaling_NaN();
-        static const bool is_signed = true;
-    };
+template <> struct numeric_limits<signed char>
+{
+    __device__ __forceinline__ static signed char min() { return SCHAR_MIN; }
+    __device__ __forceinline__ static signed char max() { return SCHAR_MAX; }
+    static const bool is_signed = true;
+};
 
-    template<> struct numeric_limits<unsigned short>
-    {
-        typedef unsigned short type;
-        __device__ __forceinline__ static type min() { return 0; };
-        __device__ __forceinline__ static type max() { return USHRT_MAX; };
-        __device__ __forceinline__ static type epsilon();
-        __device__ __forceinline__ static type round_error();
-        __device__ __forceinline__ static type denorm_min();
-        __device__ __forceinline__ static type infinity();
-        __device__ __forceinline__ static type quiet_NaN();
-        __device__ __forceinline__ static type signaling_NaN();
-        static const bool is_signed = false;
-    };
+template <> struct numeric_limits<unsigned char>
+{
+    __device__ __forceinline__ static unsigned char min() { return 0; }
+    __device__ __forceinline__ static unsigned char max() { return UCHAR_MAX; }
+    static const bool is_signed = false;
+};
 
-    template<> struct numeric_limits<int>
-    {
-        typedef int type;
-        __device__ __forceinline__ static type min() { return INT_MIN; };
-        __device__ __forceinline__ static type max() { return INT_MAX; };
-        __device__ __forceinline__ static type epsilon();
-        __device__ __forceinline__ static type round_error();
-        __device__ __forceinline__ static type denorm_min();
-        __device__ __forceinline__ static type infinity();
-        __device__ __forceinline__ static type quiet_NaN();
-        __device__ __forceinline__ static type signaling_NaN();
-        static const bool is_signed = true;
-    };
+template <> struct numeric_limits<short>
+{
+    __device__ __forceinline__ static short min() { return SHRT_MIN; }
+    __device__ __forceinline__ static short max() { return SHRT_MAX; }
+    static const bool is_signed = true;
+};
 
+template <> struct numeric_limits<unsigned short>
+{
+    __device__ __forceinline__ static unsigned short min() { return 0; }
+    __device__ __forceinline__ static unsigned short max() { return USHRT_MAX; }
+    static const bool is_signed = false;
+};
 
-    template<> struct numeric_limits<unsigned int>
-    {
-        typedef unsigned int type;
-        __device__ __forceinline__ static type min() { return 0; };
-        __device__ __forceinline__ static type max() { return UINT_MAX; };
-        __device__ __forceinline__ static type epsilon();
-        __device__ __forceinline__ static type round_error();
-        __device__ __forceinline__ static type denorm_min();
-        __device__ __forceinline__ static type infinity();
-        __device__ __forceinline__ static type quiet_NaN();
-        __device__ __forceinline__ static type signaling_NaN();
-        static const bool is_signed = false;
-    };
+template <> struct numeric_limits<int>
+{
+    __device__ __forceinline__ static int min() { return INT_MIN; }
+    __device__ __forceinline__ static int max() { return INT_MAX; }
+    static const bool is_signed = true;
+};
 
-    template<> struct numeric_limits<long>
-    {
-        typedef long type;
-        __device__ __forceinline__ static type min() { return LONG_MIN; };
-        __device__ __forceinline__ static type max() { return LONG_MAX; };
-        __device__ __forceinline__ static type epsilon();
-        __device__ __forceinline__ static type round_error();
-        __device__ __forceinline__ static type denorm_min();
-        __device__ __forceinline__ static type infinity();
-        __device__ __forceinline__ static type quiet_NaN();
-        __device__ __forceinline__ static type signaling_NaN();
-        static const bool is_signed = true;
-    };
+template <> struct numeric_limits<unsigned int>
+{
+    __device__ __forceinline__ static unsigned int min() { return 0; }
+    __device__ __forceinline__ static unsigned int max() { return UINT_MAX; }
+    static const bool is_signed = false;
+};
 
-    template<> struct numeric_limits<unsigned long>
-    {
-        typedef unsigned long type;
-        __device__ __forceinline__ static type min() { return 0; };
-        __device__ __forceinline__ static type max() { return ULONG_MAX; };
-        __device__ __forceinline__ static type epsilon();
-        __device__ __forceinline__ static type round_error();
-        __device__ __forceinline__ static type denorm_min();
-        __device__ __forceinline__ static type infinity();
-        __device__ __forceinline__ static type quiet_NaN();
-        __device__ __forceinline__ static type signaling_NaN();
-        static const bool is_signed = false;
-    };
+template <> struct numeric_limits<float>
+{
+    __device__ __forceinline__ static float min() { return FLT_MIN; }
+    __device__ __forceinline__ static float max() { return FLT_MAX; }
+    __device__ __forceinline__ static float epsilon() { return FLT_EPSILON; }
+    static const bool is_signed = true;
+};
 
-    template<> struct numeric_limits<float>
-    {
-        typedef float type;
-        __device__ __forceinline__ static type min() { return 1.175494351e-38f/*FLT_MIN*/; };
-        __device__ __forceinline__ static type max() { return 3.402823466e+38f/*FLT_MAX*/; };
-        __device__ __forceinline__ static type epsilon() { return 1.192092896e-07f/*FLT_EPSILON*/; };
-        __device__ __forceinline__ static type round_error();
-        __device__ __forceinline__ static type denorm_min();
-        __device__ __forceinline__ static type infinity();
-        __device__ __forceinline__ static type quiet_NaN();
-        __device__ __forceinline__ static type signaling_NaN();
-        static const bool is_signed = true;
-    };
+template <> struct numeric_limits<double>
+{
+    __device__ __forceinline__ static double min() { return DBL_MIN; }
+    __device__ __forceinline__ static double max() { return DBL_MAX; }
+    __device__ __forceinline__ static double epsilon() { return DBL_EPSILON; }
+    static const bool is_signed = true;
+};
 
-    template<> struct numeric_limits<double>
-    {
-        typedef double type;
-        __device__ __forceinline__ static type min() { return 2.2250738585072014e-308/*DBL_MIN*/; };
-        __device__ __forceinline__ static type max() { return 1.7976931348623158e+308/*DBL_MAX*/; };
-        __device__ __forceinline__ static type epsilon();
-        __device__ __forceinline__ static type round_error();
-        __device__ __forceinline__ static type denorm_min();
-        __device__ __forceinline__ static type infinity();
-        __device__ __forceinline__ static type quiet_NaN();
-        __device__ __forceinline__ static type signaling_NaN();
-        static const bool is_signed = true;
-    };
 }}} // namespace cv { namespace gpu { namespace device {
 
 #endif // __OPENCV_GPU_LIMITS_GPU_HPP__
diff --git a/modules/gpu/src/nvidia/core/NCV.hpp b/modules/gpu/src/nvidia/core/NCV.hpp
index 0394dba186..80e1da7953 100644
--- a/modules/gpu/src/nvidia/core/NCV.hpp
+++ b/modules/gpu/src/nvidia/core/NCV.hpp
@@ -130,7 +130,7 @@ typedef                int Ncv32s;
 typedef       unsigned int Ncv32u;
 typedef              short Ncv16s;
 typedef     unsigned short Ncv16u;
-typedef               char Ncv8s;
+typedef        signed char Ncv8s;
 typedef      unsigned char Ncv8u;
 typedef              float Ncv32f;
 typedef             double Ncv64f;
diff --git a/modules/gpu/src/nvidia/core/NCVPixelOperations.hpp b/modules/gpu/src/nvidia/core/NCVPixelOperations.hpp
index ec2f16ebb7..c1e06b434e 100644
--- a/modules/gpu/src/nvidia/core/NCVPixelOperations.hpp
+++ b/modules/gpu/src/nvidia/core/NCVPixelOperations.hpp
@@ -51,7 +51,7 @@ template<typename TBase> inline __host__ __device__ TBase _pixMaxVal();
 template<> static inline __host__ __device__ Ncv8u  _pixMaxVal<Ncv8u>()  {return UCHAR_MAX;}
 template<> static inline __host__ __device__ Ncv16u _pixMaxVal<Ncv16u>() {return USHRT_MAX;}
 template<> static inline __host__ __device__ Ncv32u _pixMaxVal<Ncv32u>() {return  UINT_MAX;}
-template<> static inline __host__ __device__ Ncv8s  _pixMaxVal<Ncv8s>()  {return  CHAR_MAX;}
+template<> static inline __host__ __device__ Ncv8s  _pixMaxVal<Ncv8s>()  {return  SCHAR_MAX;}
 template<> static inline __host__ __device__ Ncv16s _pixMaxVal<Ncv16s>() {return  SHRT_MAX;}
 template<> static inline __host__ __device__ Ncv32s _pixMaxVal<Ncv32s>() {return   INT_MAX;}
 template<> static inline __host__ __device__ Ncv32f _pixMaxVal<Ncv32f>() {return   FLT_MAX;}
@@ -61,7 +61,7 @@ template<typename TBase> inline __host__ __device__ TBase _pixMinVal();
 template<> static inline __host__ __device__ Ncv8u  _pixMinVal<Ncv8u>()  {return 0;}
 template<> static inline __host__ __device__ Ncv16u _pixMinVal<Ncv16u>() {return 0;}
 template<> static inline __host__ __device__ Ncv32u _pixMinVal<Ncv32u>() {return 0;}
-template<> static inline __host__ __device__ Ncv8s  _pixMinVal<Ncv8s>()  {return CHAR_MIN;}
+template<> static inline __host__ __device__ Ncv8s  _pixMinVal<Ncv8s>()  {return SCHAR_MIN;}
 template<> static inline __host__ __device__ Ncv16s _pixMinVal<Ncv16s>() {return SHRT_MIN;}
 template<> static inline __host__ __device__ Ncv32s _pixMinVal<Ncv32s>() {return INT_MIN;}
 template<> static inline __host__ __device__ Ncv32f _pixMinVal<Ncv32f>() {return FLT_MIN;}

From 24d84a45b19dd3d2016bacf943a3811c67e804d4 Mon Sep 17 00:00:00 2001
From: Roman Donchenko <roman.donchenko@itseez.com>
Date: Mon, 17 Jun 2013 21:06:15 +0400
Subject: [PATCH 14/27] Made tests record in the XML output which parallel
 framework was used.

---
 .../core/include/opencv2/core/internal.hpp    | 26 ++++++++++++++++++
 modules/core/src/parallel.cpp                 | 27 +++++--------------
 modules/ts/src/precomp.hpp                    |  2 ++
 modules/ts/src/ts_func.cpp                    |  8 ++++++
 4 files changed, 42 insertions(+), 21 deletions(-)

diff --git a/modules/core/include/opencv2/core/internal.hpp b/modules/core/include/opencv2/core/internal.hpp
index 5335fa01f8..10cd2caf93 100644
--- a/modules/core/include/opencv2/core/internal.hpp
+++ b/modules/core/include/opencv2/core/internal.hpp
@@ -50,6 +50,8 @@
 
 #include <vector>
 
+#include "cvconfig.h"
+
 #if defined WIN32 || defined _WIN32
 #  ifndef WIN32
 #    define WIN32
@@ -184,6 +186,30 @@ CV_INLINE IppiSize ippiSize(int width, int height)
 #  include "opencv2/core/eigen.hpp"
 #endif
 
+#ifdef _OPENMP
+#  define HAVE_OPENMP
+#endif
+
+#ifdef __APPLE__
+#  define HAVE_GCD
+#endif
+
+#if defined _MSC_VER && _MSC_VER >= 1600
+#  define HAVE_CONCURRENCY
+#endif
+
+#if defined HAVE_TBB && TBB_VERSION_MAJOR*100 + TBB_VERSION_MINOR >= 202
+#  define CV_PARALLEL_FRAMEWORK "tbb"
+#elif defined HAVE_CSTRIPES
+#  define CV_PARALLEL_FRAMEWORK "cstripes"
+#elif defined HAVE_OPENMP
+#  define CV_PARALLEL_FRAMEWORK "openmp"
+#elif defined HAVE_GCD
+#  define CV_PARALLEL_FRAMEWORK "gcd"
+#elif defined HAVE_CONCURRENCY
+#  define CV_PARALLEL_FRAMEWORK "ms-concurrency"
+#endif
+
 #ifdef __cplusplus
 
 namespace cv
diff --git a/modules/core/src/parallel.cpp b/modules/core/src/parallel.cpp
index 0b2a845ac1..51b165275f 100644
--- a/modules/core/src/parallel.cpp
+++ b/modules/core/src/parallel.cpp
@@ -61,17 +61,6 @@
     #endif
 #endif
 
-#ifdef _OPENMP
-    #define HAVE_OPENMP
-#endif
-
-#ifdef __APPLE__
-    #define HAVE_GCD
-#endif
-
-#if defined _MSC_VER && _MSC_VER >= 1600
-    #define HAVE_CONCURRENCY
-#endif
 
 /* IMPORTANT: always use the same order of defines
    1. HAVE_TBB         - 3rdparty library, should be explicitly enabled
@@ -110,10 +99,6 @@
     #endif
 #endif
 
-#if defined HAVE_TBB || defined HAVE_CSTRIPES || defined HAVE_OPENMP || defined HAVE_GCD || defined HAVE_CONCURRENCY
-   #define HAVE_PARALLEL_FRAMEWORK
-#endif
-
 namespace cv
 {
     ParallelLoopBody::~ParallelLoopBody() {}
@@ -121,7 +106,7 @@ namespace cv
 
 namespace
 {
-#ifdef HAVE_PARALLEL_FRAMEWORK
+#ifdef CV_PARALLEL_FRAMEWORK
     class ParallelLoopBodyWrapper
     {
     public:
@@ -218,7 +203,7 @@ public:
 static SchedPtr pplScheduler;
 #endif
 
-#endif // HAVE_PARALLEL_FRAMEWORK
+#endif // CV_PARALLEL_FRAMEWORK
 
 } //namespace
 
@@ -226,7 +211,7 @@ static SchedPtr pplScheduler;
 
 void cv::parallel_for_(const cv::Range& range, const cv::ParallelLoopBody& body, double nstripes)
 {
-#ifdef HAVE_PARALLEL_FRAMEWORK
+#ifdef CV_PARALLEL_FRAMEWORK
 
     if(numThreads != 0)
     {
@@ -281,7 +266,7 @@ void cv::parallel_for_(const cv::Range& range, const cv::ParallelLoopBody& body,
     }
     else
 
-#endif // HAVE_PARALLEL_FRAMEWORK
+#endif // CV_PARALLEL_FRAMEWORK
     {
         (void)nstripes;
         body(range);
@@ -290,7 +275,7 @@ void cv::parallel_for_(const cv::Range& range, const cv::ParallelLoopBody& body,
 
 int cv::getNumThreads(void)
 {
-#ifdef HAVE_PARALLEL_FRAMEWORK
+#ifdef CV_PARALLEL_FRAMEWORK
 
     if(numThreads == 0)
         return 1;
@@ -333,7 +318,7 @@ int cv::getNumThreads(void)
 void cv::setNumThreads( int threads )
 {
     (void)threads;
-#ifdef HAVE_PARALLEL_FRAMEWORK
+#ifdef CV_PARALLEL_FRAMEWORK
     numThreads = threads;
 #endif
 
diff --git a/modules/ts/src/precomp.hpp b/modules/ts/src/precomp.hpp
index 10acd7ad8f..0b2adacc4d 100644
--- a/modules/ts/src/precomp.hpp
+++ b/modules/ts/src/precomp.hpp
@@ -1,4 +1,6 @@
+#include "opencv2/core/core.hpp"
 #include "opencv2/core/core_c.h"
+#include "opencv2/core/internal.hpp"
 #include "opencv2/ts/ts.hpp"
 
 #ifdef GTEST_LINKED_AS_SHARED_LIBRARY
diff --git a/modules/ts/src/ts_func.cpp b/modules/ts/src/ts_func.cpp
index 1d636e6746..7a292d71cf 100644
--- a/modules/ts/src/ts_func.cpp
+++ b/modules/ts/src/ts_func.cpp
@@ -2958,6 +2958,14 @@ void printVersionInfo(bool useStdOut)
         ::testing::Test::RecordProperty("inner_version", ver);
         if(useStdOut) std::cout << ver << std::endl;
     }
+
+#ifdef CV_PARALLEL_FRAMEWORK
+    ::testing::Test::RecordProperty("cv_parallel_framework", CV_PARALLEL_FRAMEWORK);
+    if (useStdOut)
+    {
+        std::cout << "Parallel framework: " << CV_PARALLEL_FRAMEWORK << std::endl;
+    }
+#endif
 }
 
 } //namespace cvtest

From 4af7d65224f23739176c49341d8bcf795a8ab5ea Mon Sep 17 00:00:00 2001
From: Roman Donchenko <roman.donchenko@itseez.com>
Date: Tue, 18 Jun 2013 18:08:38 +0400
Subject: [PATCH 15/27] Made tests record information about CPU features and
 Tegra optimization status.

---
 modules/ts/src/ts_func.cpp | 42 ++++++++++++++++++++++++++++++++++++++
 1 file changed, 42 insertions(+)

diff --git a/modules/ts/src/ts_func.cpp b/modules/ts/src/ts_func.cpp
index 7a292d71cf..e2998149d5 100644
--- a/modules/ts/src/ts_func.cpp
+++ b/modules/ts/src/ts_func.cpp
@@ -2,6 +2,10 @@
 #include <float.h>
 #include <limits.h>
 
+#ifdef HAVE_TEGRA_OPTIMIZATION
+#include "tegra.hpp"
+#endif
+
 using namespace cv;
 
 namespace cvtest
@@ -2966,6 +2970,44 @@ void printVersionInfo(bool useStdOut)
         std::cout << "Parallel framework: " << CV_PARALLEL_FRAMEWORK << std::endl;
     }
 #endif
+
+    std::string cpu_features;
+
+#if CV_SSE
+    if (checkHardwareSupport(CV_CPU_SSE)) cpu_features += " sse";
+#endif
+#if CV_SSE2
+    if (checkHardwareSupport(CV_CPU_SSE2)) cpu_features += " sse2";
+#endif
+#if CV_SSE3
+    if (checkHardwareSupport(CV_CPU_SSE3)) cpu_features += " sse3";
+#endif
+#if CV_SSSE3
+    if (checkHardwareSupport(CV_CPU_SSSE3)) cpu_features += " ssse3";
+#endif
+#if CV_SSE4_1
+    if (checkHardwareSupport(CV_CPU_SSE4_1)) cpu_features += " sse4.1";
+#endif
+#if CV_SSE4_2
+    if (checkHardwareSupport(CV_CPU_SSE4_2)) cpu_features += " sse4.2";
+#endif
+#if CV_AVX
+    if (checkHardwareSupport(CV_CPU_AVX)) cpu_features += " avx";
+#endif
+#if CV_NEON
+    cpu_features += " neon"; // NEON is currently not checked at runtime
+#endif
+
+    cpu_features.erase(0, 1); // erase initial space
+
+    ::testing::Test::RecordProperty("cv_cpu_features", cpu_features);
+    if (useStdOut) std::cout << "CPU features: " << cpu_features << std::endl;
+
+#ifdef HAVE_TEGRA_OPTIMIZATION
+    const char * tegra_optimization = tegra::isDeviceSupported() ? "enabled" : "disabled";
+    ::testing::Test::RecordProperty("cv_tegra_optimization", tegra_optimization);
+    if (useStdOut) std::cout << "Tegra optimization: " << tegra_optimization << std::endl;
+#endif
 }
 
 } //namespace cvtest

From 26c246140a31556fd116bb53044575a0f9b02b84 Mon Sep 17 00:00:00 2001
From: yao <bitwangyaoyao@gmail.com>
Date: Wed, 19 Jun 2013 11:20:45 +0800
Subject: [PATCH 16/27] optimize hog

---
 modules/ocl/src/hog.cpp                 | 512 +++++++++++++++--------
 modules/ocl/src/opencl/objdetect_hog.cl | 520 +++++++++++++++++-------
 2 files changed, 709 insertions(+), 323 deletions(-)

diff --git a/modules/ocl/src/hog.cpp b/modules/ocl/src/hog.cpp
index a3514586fa..3533cce69a 100644
--- a/modules/ocl/src/hog.cpp
+++ b/modules/ocl/src/hog.cpp
@@ -15,7 +15,7 @@
 // Third party copyrights are property of their respective owners.
 //
 // @Authors
-//		Wenju He, wenju@multicorewareinc.com
+//     Wenju He, wenju@multicorewareinc.com
 //
 // Redistribution and use in source and binary forms, with or without modification,
 // are permitted provided that the following conditions are met:
@@ -48,13 +48,107 @@ using namespace cv;
 using namespace cv::ocl;
 using namespace std;
 
-
 #define CELL_WIDTH 8
 #define CELL_HEIGHT 8
 #define CELLS_PER_BLOCK_X 2
 #define CELLS_PER_BLOCK_Y 2
 #define NTHREADS 256
 
+static oclMat gauss_w_lut;
+static bool hog_device_cpu;
+/* pre-compute gaussian and interp_weight lookup tables if sigma is 4.0f */
+static const float gaussian_interp_lut[] = 
+{
+    /* gaussian lut */
+    0.01831564f, 0.02926831f, 0.04393693f, 0.06196101f, 0.08208500f, 0.10215643f, 
+    0.11943297f, 0.13117145f, 0.13533528f, 0.13117145f, 0.11943297f, 0.10215643f, 
+    0.08208500f, 0.06196101f, 0.04393693f, 0.02926831f, 0.02926831f, 0.04677062f, 
+    0.07021102f, 0.09901341f, 0.13117145f, 0.16324551f, 0.19085334f, 0.20961139f, 
+    0.21626517f, 0.20961139f, 0.19085334f, 0.16324551f, 0.13117145f, 0.09901341f, 
+    0.07021102f, 0.04677062f, 0.04393693f, 0.07021102f, 0.10539922f, 0.14863673f, 
+    0.19691168f, 0.24506053f, 0.28650481f, 0.31466395f, 0.32465246f, 0.31466395f, 
+    0.28650481f, 0.24506053f, 0.19691168f, 0.14863673f, 0.10539922f, 0.07021102f, 
+    0.06196101f, 0.09901341f, 0.14863673f, 0.20961139f, 0.27768996f, 0.34559074f, 
+    0.40403652f, 0.44374731f, 0.45783335f, 0.44374731f, 0.40403652f, 0.34559074f, 
+    0.27768996f, 0.20961139f, 0.14863673f, 0.09901341f, 0.08208500f, 0.13117145f, 
+    0.19691168f, 0.27768996f, 0.36787945f, 0.45783335f, 0.53526145f, 0.58786964f, 
+    0.60653067f, 0.58786964f, 0.53526145f, 0.45783335f, 0.36787945f, 0.27768996f, 
+    0.19691168f, 0.13117145f, 0.10215643f, 0.16324551f, 0.24506053f, 0.34559074f, 
+    0.45783335f, 0.56978285f, 0.66614360f, 0.73161560f, 0.75483960f, 0.73161560f, 
+    0.66614360f, 0.56978285f, 0.45783335f, 0.34559074f, 0.24506053f, 0.16324551f, 
+    0.11943297f, 0.19085334f, 0.28650481f, 0.40403652f, 0.53526145f, 0.66614360f, 
+    0.77880079f, 0.85534531f, 0.88249689f, 0.85534531f, 0.77880079f, 0.66614360f, 
+    0.53526145f, 0.40403652f, 0.28650481f, 0.19085334f, 0.13117145f, 0.20961139f, 
+    0.31466395f, 0.44374731f, 0.58786964f, 0.73161560f, 0.85534531f, 0.93941307f, 
+    0.96923321f, 0.93941307f, 0.85534531f, 0.73161560f, 0.58786964f, 0.44374731f, 
+    0.31466395f, 0.20961139f, 0.13533528f, 0.21626517f, 0.32465246f, 0.45783335f, 
+    0.60653067f, 0.75483960f, 0.88249689f, 0.96923321f, 1.00000000f, 0.96923321f, 
+    0.88249689f, 0.75483960f, 0.60653067f, 0.45783335f, 0.32465246f, 0.21626517f, 
+    0.13117145f, 0.20961139f, 0.31466395f, 0.44374731f, 0.58786964f, 0.73161560f, 
+    0.85534531f, 0.93941307f, 0.96923321f, 0.93941307f, 0.85534531f, 0.73161560f, 
+    0.58786964f, 0.44374731f, 0.31466395f, 0.20961139f, 0.11943297f, 0.19085334f, 
+    0.28650481f, 0.40403652f, 0.53526145f, 0.66614360f, 0.77880079f, 0.85534531f, 
+    0.88249689f, 0.85534531f, 0.77880079f, 0.66614360f, 0.53526145f, 0.40403652f, 
+    0.28650481f, 0.19085334f, 0.10215643f, 0.16324551f, 0.24506053f, 0.34559074f, 
+    0.45783335f, 0.56978285f, 0.66614360f, 0.73161560f, 0.75483960f, 0.73161560f, 
+    0.66614360f, 0.56978285f, 0.45783335f, 0.34559074f, 0.24506053f, 0.16324551f, 
+    0.08208500f, 0.13117145f, 0.19691168f, 0.27768996f, 0.36787945f, 0.45783335f, 
+    0.53526145f, 0.58786964f, 0.60653067f, 0.58786964f, 0.53526145f, 0.45783335f, 
+    0.36787945f, 0.27768996f, 0.19691168f, 0.13117145f, 0.06196101f, 0.09901341f, 
+    0.14863673f, 0.20961139f, 0.27768996f, 0.34559074f, 0.40403652f, 0.44374731f, 
+    0.45783335f, 0.44374731f, 0.40403652f, 0.34559074f, 0.27768996f, 0.20961139f, 
+    0.14863673f, 0.09901341f, 0.04393693f, 0.07021102f, 0.10539922f, 0.14863673f, 
+    0.19691168f, 0.24506053f, 0.28650481f, 0.31466395f, 0.32465246f, 0.31466395f, 
+    0.28650481f, 0.24506053f, 0.19691168f, 0.14863673f, 0.10539922f, 0.07021102f, 
+    0.02926831f, 0.04677062f, 0.07021102f, 0.09901341f, 0.13117145f, 0.16324551f, 
+    0.19085334f, 0.20961139f, 0.21626517f, 0.20961139f, 0.19085334f, 0.16324551f, 
+    0.13117145f, 0.09901341f, 0.07021102f, 0.04677062f, 
+    /* interp_weight lut */
+    0.00390625f, 0.01171875f, 0.01953125f, 0.02734375f, 0.03515625f, 0.04296875f, 
+    0.05078125f, 0.05859375f, 0.05859375f, 0.05078125f, 0.04296875f, 0.03515625f, 
+    0.02734375f, 0.01953125f, 0.01171875f, 0.00390625f, 0.01171875f, 0.03515625f, 
+    0.05859375f, 0.08203125f, 0.10546875f, 0.12890625f, 0.15234375f, 0.17578125f, 
+    0.17578125f, 0.15234375f, 0.12890625f, 0.10546875f, 0.08203125f, 0.05859375f, 
+    0.03515625f, 0.01171875f, 0.01953125f, 0.05859375f, 0.09765625f, 0.13671875f, 
+    0.17578125f, 0.21484375f, 0.25390625f, 0.29296875f, 0.29296875f, 0.25390625f, 
+    0.21484375f, 0.17578125f, 0.13671875f, 0.09765625f, 0.05859375f, 0.01953125f, 
+    0.02734375f, 0.08203125f, 0.13671875f, 0.19140625f, 0.24609375f, 0.30078125f, 
+    0.35546875f, 0.41015625f, 0.41015625f, 0.35546875f, 0.30078125f, 0.24609375f, 
+    0.19140625f, 0.13671875f, 0.08203125f, 0.02734375f, 0.03515625f, 0.10546875f, 
+    0.17578125f, 0.24609375f, 0.31640625f, 0.38671875f, 0.45703125f, 0.52734375f, 
+    0.52734375f, 0.45703125f, 0.38671875f, 0.31640625f, 0.24609375f, 0.17578125f, 
+    0.10546875f, 0.03515625f, 0.04296875f, 0.12890625f, 0.21484375f, 0.30078125f, 
+    0.38671875f, 0.47265625f, 0.55859375f, 0.64453125f, 0.64453125f, 0.55859375f, 
+    0.47265625f, 0.38671875f, 0.30078125f, 0.21484375f, 0.12890625f, 0.04296875f, 
+    0.05078125f, 0.15234375f, 0.25390625f, 0.35546875f, 0.45703125f, 0.55859375f, 
+    0.66015625f, 0.76171875f, 0.76171875f, 0.66015625f, 0.55859375f, 0.45703125f, 
+    0.35546875f, 0.25390625f, 0.15234375f, 0.05078125f, 0.05859375f, 0.17578125f, 
+    0.29296875f, 0.41015625f, 0.52734375f, 0.64453125f, 0.76171875f, 0.87890625f, 
+    0.87890625f, 0.76171875f, 0.64453125f, 0.52734375f, 0.41015625f, 0.29296875f, 
+    0.17578125f, 0.05859375f, 0.05859375f, 0.17578125f, 0.29296875f, 0.41015625f, 
+    0.52734375f, 0.64453125f, 0.76171875f, 0.87890625f, 0.87890625f, 0.76171875f, 
+    0.64453125f, 0.52734375f, 0.41015625f, 0.29296875f, 0.17578125f, 0.05859375f, 
+    0.05078125f, 0.15234375f, 0.25390625f, 0.35546875f, 0.45703125f, 0.55859375f, 
+    0.66015625f, 0.76171875f, 0.76171875f, 0.66015625f, 0.55859375f, 0.45703125f, 
+    0.35546875f, 0.25390625f, 0.15234375f, 0.05078125f, 0.04296875f, 0.12890625f, 
+    0.21484375f, 0.30078125f, 0.38671875f, 0.47265625f, 0.55859375f, 0.64453125f, 
+    0.64453125f, 0.55859375f, 0.47265625f, 0.38671875f, 0.30078125f, 0.21484375f, 
+    0.12890625f, 0.04296875f, 0.03515625f, 0.10546875f, 0.17578125f, 0.24609375f, 
+    0.31640625f, 0.38671875f, 0.45703125f, 0.52734375f, 0.52734375f, 0.45703125f, 
+    0.38671875f, 0.31640625f, 0.24609375f, 0.17578125f, 0.10546875f, 0.03515625f, 
+    0.02734375f, 0.08203125f, 0.13671875f, 0.19140625f, 0.24609375f, 0.30078125f, 
+    0.35546875f, 0.41015625f, 0.41015625f, 0.35546875f, 0.30078125f, 0.24609375f, 
+    0.19140625f, 0.13671875f, 0.08203125f, 0.02734375f, 0.01953125f, 0.05859375f, 
+    0.09765625f, 0.13671875f, 0.17578125f, 0.21484375f, 0.25390625f, 0.29296875f, 
+    0.29296875f, 0.25390625f, 0.21484375f, 0.17578125f, 0.13671875f, 0.09765625f, 
+    0.05859375f, 0.01953125f, 0.01171875f, 0.03515625f, 0.05859375f, 0.08203125f, 
+    0.10546875f, 0.12890625f, 0.15234375f, 0.17578125f, 0.17578125f, 0.15234375f, 
+    0.12890625f, 0.10546875f, 0.08203125f, 0.05859375f, 0.03515625f, 0.01171875f, 
+    0.00390625f, 0.01171875f, 0.01953125f, 0.02734375f, 0.03515625f, 0.04296875f, 
+    0.05078125f, 0.05859375f, 0.05859375f, 0.05078125f, 0.04296875f, 0.03515625f, 
+    0.02734375f, 0.01953125f, 0.01171875f, 0.00390625f
+};
+
 namespace cv
 {
     namespace ocl
@@ -78,38 +172,43 @@ namespace cv
                 int cnblocks_win_x;
                 int cnblocks_win_y;
                 int cblock_hist_size;
-                int cblock_hist_size_2up;
                 int cdescr_size;
                 int cdescr_width;
+                int cdescr_height;
 
                 void set_up_constants(int nbins, int block_stride_x, int block_stride_y,
                                       int nblocks_win_x, int nblocks_win_y);
 
                 void compute_hists(int nbins, int block_stride_x, int blovck_stride_y,
-                                   int height, int width, const cv::ocl::oclMat &grad,
-                                   const cv::ocl::oclMat &qangle, float sigma, cv::ocl::oclMat &block_hists);
+                                   int height, int width, float sigma, const cv::ocl::oclMat &grad,
+                                   const cv::ocl::oclMat &qangle, 
+                                   const cv::ocl::oclMat &gauss_w_lut, cv::ocl::oclMat &block_hists);
 
                 void normalize_hists(int nbins, int block_stride_x, int block_stride_y,
-                                     int height, int width, cv::ocl::oclMat &block_hists, float threshold);
+                                     int height, int width, cv::ocl::oclMat &block_hists, 
+                                     float threshold);
 
                 void classify_hists(int win_height, int win_width, int block_stride_y,
-                                    int block_stride_x, int win_stride_y, int win_stride_x, int height,
-                                    int width, const cv::ocl::oclMat &block_hists, const cv::ocl::oclMat &coefs, float free_coef,
+                                    int block_stride_x, int win_stride_y, int win_stride_x, 
+                                    int height, int width, const cv::ocl::oclMat &block_hists, 
+                                    const cv::ocl::oclMat &coefs, float free_coef,
                                     float threshold, cv::ocl::oclMat &labels);
 
-                void extract_descrs_by_rows(int win_height, int win_width, int block_stride_y, int block_stride_x,
-                                            int win_stride_y, int win_stride_x, int height, int width, const cv::ocl::oclMat &block_hists,
+                void extract_descrs_by_rows(int win_height, int win_width, int block_stride_y, 
+                                            int block_stride_x, int win_stride_y, int win_stride_x, 
+                                            int height, int width, const cv::ocl::oclMat &block_hists,
                                             cv::ocl::oclMat &descriptors);
-                void extract_descrs_by_cols(int win_height, int win_width, int block_stride_y, int block_stride_x,
-                                            int win_stride_y, int win_stride_x, int height, int width, const cv::ocl::oclMat &block_hists,
+                void extract_descrs_by_cols(int win_height, int win_width, int block_stride_y, 
+                                            int block_stride_x, int win_stride_y, int win_stride_x, 
+                                            int height, int width, const cv::ocl::oclMat &block_hists,
                                             cv::ocl::oclMat &descriptors);
 
                 void compute_gradients_8UC1(int height, int width, const cv::ocl::oclMat &img,
-                                            float angle_scale, cv::ocl::oclMat &grad, cv::ocl::oclMat &qangle, bool correct_gamma);
+                                            float angle_scale, cv::ocl::oclMat &grad, 
+                                            cv::ocl::oclMat &qangle, bool correct_gamma);
                 void compute_gradients_8UC4(int height, int width, const cv::ocl::oclMat &img,
-                                            float angle_scale, cv::ocl::oclMat &grad, cv::ocl::oclMat &qangle, bool correct_gamma);
-
-                void resize( const oclMat &src, oclMat &dst, const Size sz);
+                                            float angle_scale, cv::ocl::oclMat &grad, 
+                                            cv::ocl::oclMat &qangle, bool correct_gamma);
             }
         }
     }
@@ -117,8 +216,14 @@ namespace cv
 
 using namespace ::cv::ocl::device;
 
-cv::ocl::HOGDescriptor::HOGDescriptor(Size win_size_, Size block_size_, Size block_stride_, Size cell_size_,
-                                      int nbins_, double win_sigma_, double threshold_L2hys_, bool gamma_correction_, int nlevels_)
+static inline int divUp(int total, int grain)
+{
+    return (total + grain - 1) / grain;
+}
+
+cv::ocl::HOGDescriptor::HOGDescriptor(Size win_size_, Size block_size_, Size block_stride_, 
+                                      Size cell_size_, int nbins_, double win_sigma_, 
+                                      double threshold_L2hys_, bool gamma_correction_, int nlevels_)
     : win_size(win_size_),
       block_size(block_size_),
       block_stride(block_stride_),
@@ -132,19 +237,27 @@ cv::ocl::HOGDescriptor::HOGDescriptor(Size win_size_, Size block_size_, Size blo
     CV_Assert((win_size.width  - block_size.width ) % block_stride.width  == 0 &&
               (win_size.height - block_size.height) % block_stride.height == 0);
 
-    CV_Assert(block_size.width % cell_size.width == 0 && block_size.height % cell_size.height == 0);
+    CV_Assert(block_size.width % cell_size.width == 0 && 
+        block_size.height % cell_size.height == 0);
 
     CV_Assert(block_stride == cell_size);
 
     CV_Assert(cell_size == Size(8, 8));
 
-    Size cells_per_block = Size(block_size.width / cell_size.width, block_size.height / cell_size.height);
+    Size cells_per_block(block_size.width / cell_size.width, 
+        block_size.height / cell_size.height);
     CV_Assert(cells_per_block == Size(2, 2));
 
     cv::Size blocks_per_win = numPartsWithin(win_size, block_size, block_stride);
-    hog::set_up_constants(nbins, block_stride.width, block_stride.height, blocks_per_win.width, blocks_per_win.height);
+    hog::set_up_constants(nbins, block_stride.width, block_stride.height, 
+        blocks_per_win.width, blocks_per_win.height);
 
     effect_size = Size(0, 0);
+
+	if (queryDeviceInfo<IS_CPU_DEVICE, bool>())
+        hog_device_cpu = true;
+    else
+        hog_device_cpu = false;
 }
 
 size_t cv::ocl::HOGDescriptor::getDescriptorSize() const
@@ -154,7 +267,8 @@ size_t cv::ocl::HOGDescriptor::getDescriptorSize() const
 
 size_t cv::ocl::HOGDescriptor::getBlockHistogramSize() const
 {
-    Size cells_per_block = Size(block_size.width / cell_size.width, block_size.height / cell_size.height);
+    Size cells_per_block = Size(block_size.width / cell_size.width, 
+        block_size.height / cell_size.height);
     return (size_t)(nbins * cells_per_block.area());
 }
 
@@ -167,7 +281,8 @@ bool cv::ocl::HOGDescriptor::checkDetectorSize() const
 {
     size_t detector_size = detector.rows * detector.cols;
     size_t descriptor_size = getDescriptorSize();
-    return detector_size == 0 || detector_size == descriptor_size || detector_size == descriptor_size + 1;
+    return detector_size == 0 || detector_size == descriptor_size || 
+        detector_size == descriptor_size + 1;
 }
 
 void cv::ocl::HOGDescriptor::setSVMDetector(const vector<float> &_detector)
@@ -207,10 +322,16 @@ void cv::ocl::HOGDescriptor::init_buffer(const oclMat &img, Size win_stride)
 
     const size_t block_hist_size = getBlockHistogramSize();
     const Size blocks_per_img = numPartsWithin(img.size(), block_size, block_stride);
-    block_hists.create(1, static_cast<int>(block_hist_size * blocks_per_img.area()), CV_32F);
+    block_hists.create(1, 
+        static_cast<int>(block_hist_size * blocks_per_img.area()) + 256, CV_32F);
 
     Size wins_per_img = numPartsWithin(img.size(), win_size, win_stride);
     labels.create(1, wins_per_img.area(), CV_8U);
+
+    vector<float> v_lut = vector<float>(gaussian_interp_lut, gaussian_interp_lut + 
+        sizeof(gaussian_interp_lut) / sizeof(gaussian_interp_lut[0]));
+    Mat m_lut(v_lut);
+    gauss_w_lut.upload(m_lut.reshape(1,1));
 }
 
 void cv::ocl::HOGDescriptor::computeGradient(const oclMat &img, oclMat &grad, oclMat &qangle)
@@ -221,29 +342,34 @@ void cv::ocl::HOGDescriptor::computeGradient(const oclMat &img, oclMat &grad, oc
     switch (img.type())
     {
     case CV_8UC1:
-        hog::compute_gradients_8UC1(effect_size.height, effect_size.width, img, angleScale, grad, qangle, gamma_correction);
+        hog::compute_gradients_8UC1(effect_size.height, effect_size.width, img, 
+            angleScale, grad, qangle, gamma_correction);
         break;
     case CV_8UC4:
-        hog::compute_gradients_8UC4(effect_size.height, effect_size.width, img, angleScale, grad, qangle, gamma_correction);
+        hog::compute_gradients_8UC4(effect_size.height, effect_size.width, img, 
+            angleScale, grad, qangle, gamma_correction);
         break;
     }
 }
 
+
 void cv::ocl::HOGDescriptor::computeBlockHistograms(const oclMat &img)
 {
-    computeGradient(img, grad, qangle);
+    computeGradient(img, this->grad, this->qangle);
 
-    hog::compute_hists(nbins, block_stride.width, block_stride.height, effect_size.height, effect_size.width,
-                       grad, qangle, (float)getWinSigma(), block_hists);
+    hog::compute_hists(nbins, block_stride.width, block_stride.height, effect_size.height, 
+        effect_size.width, (float)getWinSigma(), grad, qangle, gauss_w_lut, block_hists);
 
-    hog::normalize_hists(nbins, block_stride.width, block_stride.height, effect_size.height, effect_size.width,
-                         block_hists, (float)threshold_L2hys);
+    hog::normalize_hists(nbins, block_stride.width, block_stride.height, effect_size.height, 
+        effect_size.width, block_hists, (float)threshold_L2hys);
 }
 
 
-void cv::ocl::HOGDescriptor::getDescriptors(const oclMat &img, Size win_stride, oclMat &descriptors, int descr_format)
+void cv::ocl::HOGDescriptor::getDescriptors(const oclMat &img, Size win_stride, 
+                                            oclMat &descriptors, int descr_format)
 {
-    CV_Assert(win_stride.width % block_stride.width == 0 && win_stride.height % block_stride.height == 0);
+    CV_Assert(win_stride.width % block_stride.width == 0 && 
+        win_stride.height % block_stride.height == 0);
 
     init_buffer(img, win_stride);
 
@@ -253,17 +379,20 @@ void cv::ocl::HOGDescriptor::getDescriptors(const oclMat &img, Size win_stride,
     Size blocks_per_win = numPartsWithin(win_size, block_size, block_stride);
     Size wins_per_img   = numPartsWithin(effect_size, win_size, win_stride);
 
-    descriptors.create(wins_per_img.area(), static_cast<int>(blocks_per_win.area() * block_hist_size), CV_32F);
+    descriptors.create(wins_per_img.area(), 
+        static_cast<int>(blocks_per_win.area() * block_hist_size), CV_32F);
 
     switch (descr_format)
     {
     case DESCR_FORMAT_ROW_BY_ROW:
-        hog::extract_descrs_by_rows(win_size.height, win_size.width, block_stride.height, block_stride.width,
-                                    win_stride.height, win_stride.width, effect_size.height, effect_size.width, block_hists, descriptors);
+        hog::extract_descrs_by_rows(win_size.height, win_size.width, 
+            block_stride.height, block_stride.width, win_stride.height, win_stride.width, 
+            effect_size.height, effect_size.width, block_hists, descriptors);
         break;
     case DESCR_FORMAT_COL_BY_COL:
-        hog::extract_descrs_by_cols(win_size.height, win_size.width, block_stride.height, block_stride.width,
-                                    win_stride.height, win_stride.width, effect_size.height, effect_size.width, block_hists, descriptors);
+        hog::extract_descrs_by_cols(win_size.height, win_size.width, 
+            block_stride.height, block_stride.width, win_stride.height, win_stride.width, 
+            effect_size.height, effect_size.width, block_hists, descriptors);
         break;
     default:
         CV_Error(CV_StsBadArg, "Unknown descriptor format");
@@ -271,7 +400,8 @@ void cv::ocl::HOGDescriptor::getDescriptors(const oclMat &img, Size win_stride,
 }
 
 
-void cv::ocl::HOGDescriptor::detect(const oclMat &img, vector<Point> &hits, double hit_threshold, Size win_stride, Size padding)
+void cv::ocl::HOGDescriptor::detect(const oclMat &img, vector<Point> &hits, 
+                                    double hit_threshold, Size win_stride, Size padding)
 {
     CV_Assert(img.type() == CV_8UC1 || img.type() == CV_8UC4);
     CV_Assert(padding == Size(0, 0));
@@ -283,14 +413,16 @@ void cv::ocl::HOGDescriptor::detect(const oclMat &img, vector<Point> &hits, doub
     if (win_stride == Size())
         win_stride = block_stride;
     else
-        CV_Assert(win_stride.width % block_stride.width == 0 && win_stride.height % block_stride.height == 0);
+        CV_Assert(win_stride.width % block_stride.width == 0 && 
+            win_stride.height % block_stride.height == 0);
     init_buffer(img, win_stride);
 
     computeBlockHistograms(img);
 
-    hog::classify_hists(win_size.height, win_size.width, block_stride.height, block_stride.width,
-                        win_stride.height, win_stride.width, effect_size.height, effect_size.width, block_hists,
-                        detector, (float)free_coef, (float)hit_threshold, labels);
+    hog::classify_hists(win_size.height, win_size.width, block_stride.height, 
+        block_stride.width, win_stride.height, win_stride.width, 
+        effect_size.height, effect_size.width, block_hists, detector, 
+        (float)free_coef, (float)hit_threshold, labels);
 
     labels.download(labels_host);
     unsigned char *vec = labels_host.ptr();
@@ -306,8 +438,9 @@ void cv::ocl::HOGDescriptor::detect(const oclMat &img, vector<Point> &hits, doub
 
 
 
-void cv::ocl::HOGDescriptor::detectMultiScale(const oclMat &img, vector<Rect> &found_locations, double hit_threshold,
-        Size win_stride, Size padding, double scale0, int group_threshold)
+void cv::ocl::HOGDescriptor::detectMultiScale(const oclMat &img, vector<Rect> &found_locations, 
+                                              double hit_threshold, Size win_stride, Size padding, 
+                                              double scale0, int group_threshold)
 {
     CV_Assert(img.type() == CV_8UC1 || img.type() == CV_8UC4);
     CV_Assert(scale0 > 1);
@@ -333,7 +466,8 @@ void cv::ocl::HOGDescriptor::detectMultiScale(const oclMat &img, vector<Rect> &f
     if (win_stride == Size())
         win_stride = block_stride;
     else
-        CV_Assert(win_stride.width % block_stride.width == 0 && win_stride.height % block_stride.height == 0);
+        CV_Assert(win_stride.width % block_stride.width == 0 && 
+            win_stride.height % block_stride.height == 0);
     init_buffer(img, win_stride);
     image_scale.create(img.size(), img.type());
 
@@ -347,16 +481,18 @@ void cv::ocl::HOGDescriptor::detectMultiScale(const oclMat &img, vector<Rect> &f
         }
         else
         {
-            hog::resize( img, image_scale, effect_size);
+            resize(img, image_scale, effect_size);
             detect(image_scale, locations, hit_threshold, win_stride, padding);
         }
-        Size scaled_win_size(cvRound(win_size.width * scale), cvRound(win_size.height * scale));
+        Size scaled_win_size(cvRound(win_size.width * scale), 
+            cvRound(win_size.height * scale));
         for (size_t j = 0; j < locations.size(); j++)
-            all_candidates.push_back(Rect(Point2d((CvPoint)locations[j]) * scale, scaled_win_size));
+            all_candidates.push_back(Rect(Point2d((CvPoint)locations[j]) * scale, 
+              scaled_win_size));
     }
 
     found_locations.assign(all_candidates.begin(), all_candidates.end());
-    groupRectangles(found_locations, group_threshold, 0.2/*magic number copied from CPU version*/);
+    groupRectangles(found_locations, group_threshold, 0.2);
 }
 
 int cv::ocl::HOGDescriptor::numPartsWithin(int size, int part_size, int stride)
@@ -364,9 +500,11 @@ int cv::ocl::HOGDescriptor::numPartsWithin(int size, int part_size, int stride)
     return (size - part_size + stride) / stride;
 }
 
-cv::Size cv::ocl::HOGDescriptor::numPartsWithin(cv::Size size, cv::Size part_size, cv::Size stride)
+cv::Size cv::ocl::HOGDescriptor::numPartsWithin(cv::Size size, cv::Size part_size, 
+                                                cv::Size stride)
 {
-    return Size(numPartsWithin(size.width, part_size.width, stride.width), numPartsWithin(size.height, part_size.height, stride.height));
+    return Size(numPartsWithin(size.width, part_size.width, stride.width), 
+        numPartsWithin(size.height, part_size.height, stride.height));
 }
 
 std::vector<float> cv::ocl::HOGDescriptor::getDefaultPeopleDetector()
@@ -1547,8 +1685,9 @@ static int power_2up(unsigned int n)
     return -1; // Input is too big
 }
 
-void cv::ocl::device::hog::set_up_constants(int nbins, int block_stride_x, int block_stride_y,
-        int nblocks_win_x, int nblocks_win_y)
+void cv::ocl::device::hog::set_up_constants(int nbins, 
+                                            int block_stride_x, int block_stride_y, 
+                                            int nblocks_win_x, int nblocks_win_y)
 {
     cnbins = nbins;
     cblock_stride_x = block_stride_x;
@@ -1559,53 +1698,32 @@ void cv::ocl::device::hog::set_up_constants(int nbins, int block_stride_x, int b
     int block_hist_size = nbins * CELLS_PER_BLOCK_X * CELLS_PER_BLOCK_Y;
     cblock_hist_size = block_hist_size;
 
-    int block_hist_size_2up = power_2up(block_hist_size);
-    cblock_hist_size_2up = block_hist_size_2up;
-
     int descr_width = nblocks_win_x * block_hist_size;
     cdescr_width = descr_width;
+    cdescr_height = nblocks_win_y;
 
     int descr_size = descr_width * nblocks_win_y;
     cdescr_size = descr_size;
 }
 
-static inline int divUp(int total, int grain)
-{
-    return (total + grain - 1) / grain;
-}
-
-static void openCLExecuteKernel_hog(Context *clCxt , const char **source, string kernelName, 
-                                    size_t globalThreads[3], size_t localThreads[3], 
-                                    vector< pair<size_t, const void *> > &args)
-{
-    cl_kernel kernel = openCLGetKernelFromSource(clCxt, source, kernelName);
-    size_t wave_size = queryDeviceInfo<WAVEFRONT_SIZE, size_t>(kernel);
-    openCLSafeCall(clReleaseKernel(kernel));
-    if (wave_size <= 16)
-    {
-        char build_options[64];
-        sprintf(build_options, (wave_size == 16) ? "-D WAVE_SIZE_16" : "-D WAVE_SIZE_1");
-        openCLExecuteKernel(clCxt, source, kernelName, globalThreads, localThreads, args, -1, -1, build_options);
-    }
-    else
-        openCLExecuteKernel(clCxt, source, kernelName, globalThreads, localThreads, args, -1, -1);
-}
-
-void cv::ocl::device::hog::compute_hists(int nbins, int block_stride_x, int block_stride_y,
-        int height, int width, const cv::ocl::oclMat &grad,
-        const cv::ocl::oclMat &qangle, float sigma, cv::ocl::oclMat &block_hists)
+void cv::ocl::device::hog::compute_hists(int nbins, 
+                                         int block_stride_x, int block_stride_y,
+                                         int height, int width, float sigma, 
+                                         const cv::ocl::oclMat &grad, 
+                                         const cv::ocl::oclMat &qangle, 
+                                         const cv::ocl::oclMat &gauss_w_lut, 
+                                         cv::ocl::oclMat &block_hists)
 {
     Context *clCxt = Context::getContext();
-    string kernelName = "compute_hists_kernel";
     vector< pair<size_t, const void *> > args;
+    string kernelName = (sigma == 4.0f) ? "compute_hists_lut_kernel" : 
+        "compute_hists_kernel";
 
-    int img_block_width = (width - CELLS_PER_BLOCK_X * CELL_WIDTH + block_stride_x) / block_stride_x;
-    int img_block_height = (height - CELLS_PER_BLOCK_Y * CELL_HEIGHT + block_stride_y) / block_stride_y;
-
+    int img_block_width = (width - CELLS_PER_BLOCK_X * CELL_WIDTH + block_stride_x) 
+        / block_stride_x;
+    int img_block_height = (height - CELLS_PER_BLOCK_Y * CELL_HEIGHT + block_stride_y) 
+        / block_stride_y;
     int blocks_total = img_block_width * img_block_height;
-    int blocks_in_group = 4;
-    size_t localThreads[3] = { blocks_in_group * 24, 2, 1 };
-    size_t globalThreads[3] = { divUp(blocks_total, blocks_in_group) * localThreads[0], 2, 1 };
 
     int grad_quadstep = grad.step >> 2;
     int qangle_step = qangle.step;
@@ -1613,6 +1731,11 @@ void cv::ocl::device::hog::compute_hists(int nbins, int block_stride_x, int bloc
     // Precompute gaussian spatial window parameter
     float scale = 1.f / (2.f * sigma * sigma);
 
+    int blocks_in_group = 4;
+    size_t localThreads[3] = { blocks_in_group * 24, 2, 1 };
+    size_t globalThreads[3] = { 
+        divUp(img_block_width * img_block_height, blocks_in_group) * localThreads[0], 2, 1 };
+
     int hists_size = (nbins * CELLS_PER_BLOCK_X * CELLS_PER_BLOCK_Y * 12) * sizeof(float);
     int final_hists_size = (nbins * CELLS_PER_BLOCK_X * CELLS_PER_BLOCK_Y) * sizeof(float);
     int smem = (hists_size + final_hists_size) * blocks_in_group;
@@ -1628,62 +1751,120 @@ void cv::ocl::device::hog::compute_hists(int nbins, int block_stride_x, int bloc
     args.push_back( make_pair( sizeof(cl_int), (void *)&qangle_step));
     args.push_back( make_pair( sizeof(cl_mem), (void *)&grad.data));
     args.push_back( make_pair( sizeof(cl_mem), (void *)&qangle.data));
-    args.push_back( make_pair( sizeof(cl_float), (void *)&scale));
+    if (kernelName.compare("compute_hists_lut_kernel") == 0)
+        args.push_back( make_pair( sizeof(cl_mem), (void *)&gauss_w_lut.data));
+    else
+        args.push_back( make_pair( sizeof(cl_float), (void *)&scale));
     args.push_back( make_pair( sizeof(cl_mem), (void *)&block_hists.data));
     args.push_back( make_pair( smem, (void *)NULL));
 
-    openCLExecuteKernel_hog(clCxt, &objdetect_hog, kernelName, globalThreads, localThreads, args);
+    openCLExecuteKernel(clCxt, &objdetect_hog, kernelName, globalThreads, 
+        localThreads, args, -1, -1);
 }
 
-void cv::ocl::device::hog::normalize_hists(int nbins, int block_stride_x, int block_stride_y,
-        int height, int width, cv::ocl::oclMat &block_hists, float threshold)
+void cv::ocl::device::hog::normalize_hists(int nbins, 
+                                           int block_stride_x, int block_stride_y,
+                                           int height, int width, 
+                                           cv::ocl::oclMat &block_hists, 
+                                           float threshold)
 {
     Context *clCxt = Context::getContext();
-    string kernelName = "normalize_hists_kernel";
     vector< pair<size_t, const void *> > args;
+    string kernelName;
 
     int block_hist_size = nbins * CELLS_PER_BLOCK_X * CELLS_PER_BLOCK_Y;
-    int nthreads = power_2up(block_hist_size);
-
-    int img_block_width = (width - CELLS_PER_BLOCK_X * CELL_WIDTH + block_stride_x) / block_stride_x;
-    int img_block_height = (height - CELLS_PER_BLOCK_Y * CELL_HEIGHT + block_stride_y) / block_stride_y;
-    size_t globalThreads[3] = { img_block_width * nthreads, img_block_height, 1 };
-    size_t localThreads[3] = { nthreads, 1, 1  };
-
-    if ((nthreads < 32) || (nthreads > 512) )
-        cv::ocl::error("normalize_hists: histogram's size is too small or too big", __FILE__, __LINE__, "normalize_hists");
+    int img_block_width = (width - CELLS_PER_BLOCK_X * CELL_WIDTH + block_stride_x) 
+        / block_stride_x;
+    int img_block_height = (height - CELLS_PER_BLOCK_Y * CELL_HEIGHT + block_stride_y) 
+        / block_stride_y;
+    int nthreads;
+    size_t globalThreads[3] = { 1, 1, 1  };
+    size_t localThreads[3] = { 1, 1, 1  };
+    
+    if ( nbins == 9 )
+    {
+        /* optimized for the case of 9 bins */
+        kernelName = "normalize_hists_36_kernel";
+        int blocks_in_group = NTHREADS / block_hist_size;
+        nthreads = blocks_in_group * block_hist_size;
+        int num_groups = divUp( img_block_width * img_block_height, blocks_in_group);
+        globalThreads[0] = nthreads * num_groups;
+        localThreads[0] = nthreads;
+    }
+    else
+    {
+        kernelName = "normalize_hists_kernel";
+        nthreads = power_2up(block_hist_size);
+        globalThreads[0] = img_block_width * nthreads;
+        globalThreads[1] = img_block_height;
+        localThreads[0] = nthreads;
+
+        if ((nthreads < 32) || (nthreads > 512) )
+            cv::ocl::error("normalize_hists: histogram's size is too small or too big", 
+                __FILE__, __LINE__, "normalize_hists");
+
+        args.push_back( make_pair( sizeof(cl_int), (void *)&nthreads));
+        args.push_back( make_pair( sizeof(cl_int), (void *)&block_hist_size));
+        args.push_back( make_pair( sizeof(cl_int), (void *)&img_block_width));
+    }
 
-    args.push_back( make_pair( sizeof(cl_int), (void *)&nthreads));
-    args.push_back( make_pair( sizeof(cl_int), (void *)&block_hist_size));
-    args.push_back( make_pair( sizeof(cl_int), (void *)&img_block_width));
     args.push_back( make_pair( sizeof(cl_mem), (void *)&block_hists.data));
     args.push_back( make_pair( sizeof(cl_float), (void *)&threshold));
     args.push_back( make_pair( nthreads * sizeof(float), (void *)NULL));
 
-    openCLExecuteKernel_hog(clCxt, &objdetect_hog, kernelName, globalThreads, localThreads, args);
+    if(hog_device_cpu)
+        openCLExecuteKernel(clCxt, &objdetect_hog, kernelName, globalThreads, 
+                             localThreads, args, -1, -1, "-D CPU");
+    else
+        openCLExecuteKernel(clCxt, &objdetect_hog, kernelName, globalThreads, 
+                             localThreads, args, -1, -1);
 }
 
-void cv::ocl::device::hog::classify_hists(int win_height, int win_width, int block_stride_y,
-        int block_stride_x, int win_stride_y, int win_stride_x, int height,
-        int width, const cv::ocl::oclMat &block_hists, const cv::ocl::oclMat &coefs, float free_coef,
-        float threshold, cv::ocl::oclMat &labels)
+void cv::ocl::device::hog::classify_hists(int win_height, int win_width, 
+                                          int block_stride_y, int block_stride_x, 
+                                          int win_stride_y, int win_stride_x, 
+                                          int height, int width, 
+                                          const cv::ocl::oclMat &block_hists, 
+                                          const cv::ocl::oclMat &coefs, 
+                                          float free_coef, float threshold, 
+                                          cv::ocl::oclMat &labels)
 {
     Context *clCxt = Context::getContext();
-    string kernelName = "classify_hists_kernel";
     vector< pair<size_t, const void *> > args;
 
+    int nthreads;
+    string kernelName;
+    switch (cdescr_width)
+    {
+    case 180:
+        nthreads = 180;
+        kernelName = "classify_hists_180_kernel";
+        args.push_back( make_pair( sizeof(cl_int), (void *)&cdescr_width));
+        args.push_back( make_pair( sizeof(cl_int), (void *)&cdescr_height));
+        break;
+    case 252:
+        nthreads = 256;
+        kernelName = "classify_hists_252_kernel";
+        args.push_back( make_pair( sizeof(cl_int), (void *)&cdescr_width));
+        args.push_back( make_pair( sizeof(cl_int), (void *)&cdescr_height));
+        break;
+    default:
+        nthreads = 256;
+        kernelName = "classify_hists_kernel";
+        args.push_back( make_pair( sizeof(cl_int), (void *)&cdescr_size));
+        args.push_back( make_pair( sizeof(cl_int), (void *)&cdescr_width));
+    }
+
     int win_block_stride_x = win_stride_x / block_stride_x;
     int win_block_stride_y = win_stride_y / block_stride_y;
     int img_win_width = (width - win_width + win_stride_x) / win_stride_x;
     int img_win_height = (height - win_height + win_stride_y) / win_stride_y;
-    int img_block_width = (width - CELLS_PER_BLOCK_X * CELL_WIDTH + block_stride_x) / block_stride_x;
-
-    size_t globalThreads[3] = { img_win_width * NTHREADS, img_win_height, 1 };
-    size_t localThreads[3] = { NTHREADS, 1, 1 };
+    int img_block_width = (width - CELLS_PER_BLOCK_X * CELL_WIDTH + block_stride_x) / 
+        block_stride_x;
 
+    size_t globalThreads[3] = { img_win_width * nthreads, img_win_height, 1 };
+    size_t localThreads[3] = { nthreads, 1, 1 };
     args.push_back( make_pair( sizeof(cl_int), (void *)&cblock_hist_size));
-    args.push_back( make_pair( sizeof(cl_int), (void *)&cdescr_size));
-    args.push_back( make_pair( sizeof(cl_int), (void *)&cdescr_width));
     args.push_back( make_pair( sizeof(cl_int), (void *)&img_win_width));
     args.push_back( make_pair( sizeof(cl_int), (void *)&img_block_width));
     args.push_back( make_pair( sizeof(cl_int), (void *)&win_block_stride_x));
@@ -1694,12 +1875,20 @@ void cv::ocl::device::hog::classify_hists(int win_height, int win_width, int blo
     args.push_back( make_pair( sizeof(cl_float), (void *)&threshold));
     args.push_back( make_pair( sizeof(cl_mem), (void *)&labels.data));
 
-    openCLExecuteKernel_hog(clCxt, &objdetect_hog, kernelName, globalThreads, localThreads, args);
+    if(hog_device_cpu)
+        openCLExecuteKernel(clCxt, &objdetect_hog, kernelName, globalThreads, 
+                             localThreads, args, -1, -1, "-D CPU");
+    else
+        openCLExecuteKernel(clCxt, &objdetect_hog, kernelName, globalThreads, 
+                             localThreads, args, -1, -1);
 }
 
-void cv::ocl::device::hog::extract_descrs_by_rows(int win_height, int win_width, int block_stride_y, int block_stride_x,
-        int win_stride_y, int win_stride_x, int height, int width,
-        const cv::ocl::oclMat &block_hists, cv::ocl::oclMat &descriptors)
+void cv::ocl::device::hog::extract_descrs_by_rows(int win_height, int win_width, 
+                                                  int block_stride_y, int block_stride_x,
+                                                  int win_stride_y, int win_stride_x, 
+                                                  int height, int width,
+                                                  const cv::ocl::oclMat &block_hists, 
+                                                  cv::ocl::oclMat &descriptors)
 {
     Context *clCxt = Context::getContext();
     string kernelName = "extract_descrs_by_rows_kernel";
@@ -1709,7 +1898,8 @@ void cv::ocl::device::hog::extract_descrs_by_rows(int win_height, int win_width,
     int win_block_stride_y = win_stride_y / block_stride_y;
     int img_win_width = (width - win_width + win_stride_x) / win_stride_x;
     int img_win_height = (height - win_height + win_stride_y) / win_stride_y;
-    int img_block_width = (width - CELLS_PER_BLOCK_X * CELL_WIDTH + block_stride_x) / block_stride_x;
+    int img_block_width = (width - CELLS_PER_BLOCK_X * CELL_WIDTH + block_stride_x) / 
+        block_stride_x;
     int descriptors_quadstep = descriptors.step >> 2;
 
     size_t globalThreads[3] = { img_win_width * NTHREADS, img_win_height, 1 };
@@ -1725,12 +1915,16 @@ void cv::ocl::device::hog::extract_descrs_by_rows(int win_height, int win_width,
     args.push_back( make_pair( sizeof(cl_mem), (void *)&block_hists.data));
     args.push_back( make_pair( sizeof(cl_mem), (void *)&descriptors.data));
 
-    openCLExecuteKernel(clCxt, &objdetect_hog, kernelName, globalThreads, localThreads, args, -1, -1);
+    openCLExecuteKernel(clCxt, &objdetect_hog, kernelName, globalThreads, 
+        localThreads, args, -1, -1);
 }
 
-void cv::ocl::device::hog::extract_descrs_by_cols(int win_height, int win_width, int block_stride_y, int block_stride_x,
-        int win_stride_y, int win_stride_x, int height, int width,
-        const cv::ocl::oclMat &block_hists, cv::ocl::oclMat &descriptors)
+void cv::ocl::device::hog::extract_descrs_by_cols(int win_height, int win_width, 
+                                                  int block_stride_y, int block_stride_x,
+                                                  int win_stride_y, int win_stride_x, 
+                                                  int height, int width,
+                                                  const cv::ocl::oclMat &block_hists, 
+                                                  cv::ocl::oclMat &descriptors)
 {
     Context *clCxt = Context::getContext();
     string kernelName = "extract_descrs_by_cols_kernel";
@@ -1740,7 +1934,8 @@ void cv::ocl::device::hog::extract_descrs_by_cols(int win_height, int win_width,
     int win_block_stride_y = win_stride_y / block_stride_y;
     int img_win_width = (width - win_width + win_stride_x) / win_stride_x;
     int img_win_height = (height - win_height + win_stride_y) / win_stride_y;
-    int img_block_width = (width - CELLS_PER_BLOCK_X * CELL_WIDTH + block_stride_x) / block_stride_x;
+    int img_block_width = (width - CELLS_PER_BLOCK_X * CELL_WIDTH + block_stride_x) / 
+        block_stride_x;
     int descriptors_quadstep = descriptors.step >> 2;
 
     size_t globalThreads[3] = { img_win_width * NTHREADS, img_win_height, 1 };
@@ -1757,11 +1952,16 @@ void cv::ocl::device::hog::extract_descrs_by_cols(int win_height, int win_width,
     args.push_back( make_pair( sizeof(cl_mem), (void *)&block_hists.data));
     args.push_back( make_pair( sizeof(cl_mem), (void *)&descriptors.data));
 
-    openCLExecuteKernel(clCxt, &objdetect_hog, kernelName, globalThreads, localThreads, args, -1, -1);
+    openCLExecuteKernel(clCxt, &objdetect_hog, kernelName, globalThreads, 
+        localThreads, args, -1, -1);
 }
 
-void cv::ocl::device::hog::compute_gradients_8UC1(int height, int width, const cv::ocl::oclMat &img,
-        float angle_scale, cv::ocl::oclMat &grad, cv::ocl::oclMat &qangle, bool correct_gamma)
+void cv::ocl::device::hog::compute_gradients_8UC1(int height, int width, 
+                                                  const cv::ocl::oclMat &img,
+                                                  float angle_scale, 
+                                                  cv::ocl::oclMat &grad, 
+                                                  cv::ocl::oclMat &qangle, 
+                                                  bool correct_gamma)
 {
     Context *clCxt = Context::getContext();
     string kernelName = "compute_gradients_8UC1_kernel";
@@ -1786,11 +1986,16 @@ void cv::ocl::device::hog::compute_gradients_8UC1(int height, int width, const c
     args.push_back( make_pair( sizeof(cl_char), (void *)&correctGamma));
     args.push_back( make_pair( sizeof(cl_int), (void *)&cnbins));
 
-    openCLExecuteKernel(clCxt, &objdetect_hog, kernelName, globalThreads, localThreads, args, -1, -1);
+    openCLExecuteKernel(clCxt, &objdetect_hog, kernelName, globalThreads, 
+        localThreads, args, -1, -1);
 }
 
-void cv::ocl::device::hog::compute_gradients_8UC4(int height, int width, const cv::ocl::oclMat &img,
-        float angle_scale, cv::ocl::oclMat &grad, cv::ocl::oclMat &qangle, bool correct_gamma)
+void cv::ocl::device::hog::compute_gradients_8UC4(int height, int width, 
+                                                  const cv::ocl::oclMat &img,
+                                                  float angle_scale, 
+                                                  cv::ocl::oclMat &grad, 
+                                                  cv::ocl::oclMat &qangle, 
+                                                  bool correct_gamma)
 {
     Context *clCxt = Context::getContext();
     string kernelName = "compute_gradients_8UC4_kernel";
@@ -1816,39 +2021,6 @@ void cv::ocl::device::hog::compute_gradients_8UC4(int height, int width, const c
     args.push_back( make_pair( sizeof(cl_char), (void *)&correctGamma));
     args.push_back( make_pair( sizeof(cl_int), (void *)&cnbins));
 
-    openCLExecuteKernel(clCxt, &objdetect_hog, kernelName, globalThreads, localThreads, args, -1, -1);
-}
-
-void cv::ocl::device::hog::resize( const oclMat &src, oclMat &dst, const Size sz)
-{
-    CV_Assert( (src.channels() == dst.channels()) );
-    Context *clCxt = Context::getContext();
-
-    string kernelName = (src.type() == CV_8UC1) ? "resize_8UC1_kernel" : "resize_8UC4_kernel";
-    size_t blkSizeX = 16, blkSizeY = 16;
-    size_t glbSizeX = sz.width % blkSizeX == 0 ? sz.width : (sz.width / blkSizeX + 1) * blkSizeX;
-    size_t glbSizeY = sz.height % blkSizeY == 0 ? sz.height : (sz.height / blkSizeY + 1) * blkSizeY;
-    size_t globalThreads[3] = {glbSizeX, glbSizeY, 1};
-    size_t localThreads[3] = {blkSizeX, blkSizeY, 1};
-
-    float ifx = (float)src.cols / sz.width;
-    float ify = (float)src.rows / sz.height;
-    int src_step = static_cast<int>(src.step);
-    int dst_step = static_cast<int>(dst.step);
-
-    vector< pair<size_t, const void *> > args;
-    args.push_back( make_pair(sizeof(cl_mem), (void *)&dst.data));
-    args.push_back( make_pair(sizeof(cl_mem), (void *)&src.data));
-    args.push_back( make_pair(sizeof(cl_int), (void *)&dst.offset));
-    args.push_back( make_pair(sizeof(cl_int), (void *)&src.offset));
-    args.push_back( make_pair(sizeof(cl_int), (void *)&dst_step));
-    args.push_back( make_pair(sizeof(cl_int), (void *)&src_step));
-    args.push_back( make_pair(sizeof(cl_int), (void *)&src.cols));
-    args.push_back( make_pair(sizeof(cl_int), (void *)&src.rows));
-    args.push_back( make_pair(sizeof(cl_int), (void *)&sz.width));
-    args.push_back( make_pair(sizeof(cl_int), (void *)&sz.height));
-    args.push_back( make_pair(sizeof(cl_float), (void *)&ifx));
-    args.push_back( make_pair(sizeof(cl_float), (void *)&ify));
-
-    openCLExecuteKernel(clCxt, &objdetect_hog, kernelName, globalThreads, localThreads, args, -1, -1);
-}
+    openCLExecuteKernel(clCxt, &objdetect_hog, kernelName, globalThreads, 
+        localThreads, args, -1, -1);
+}
\ No newline at end of file
diff --git a/modules/ocl/src/opencl/objdetect_hog.cl b/modules/ocl/src/opencl/objdetect_hog.cl
index 8852facae8..05d538330f 100644
--- a/modules/ocl/src/opencl/objdetect_hog.cl
+++ b/modules/ocl/src/opencl/objdetect_hog.cl
@@ -43,7 +43,6 @@
 //
 //M*/
 
-
 #define CELL_WIDTH 8
 #define CELL_HEIGHT 8
 #define CELLS_PER_BLOCK_X 2
@@ -51,6 +50,100 @@
 #define NTHREADS 256
 #define CV_PI_F 3.1415926535897932384626433832795f
 
+//----------------------------------------------------------------------------
+// Histogram computation
+// 12 threads for a cell, 12x4 threads per block
+// Use pre-computed gaussian and interp_weight lookup tables if sigma is 4.0f
+__kernel void compute_hists_lut_kernel(
+    const int cblock_stride_x, const int cblock_stride_y,
+    const int cnbins, const int cblock_hist_size, const int img_block_width, 
+    const int blocks_in_group, const int blocks_total,
+    const int grad_quadstep, const int qangle_step,
+    __global const float* grad, __global const uchar* qangle,
+    __global const float* gauss_w_lut,
+    __global float* block_hists, __local float* smem)
+{
+    const int lx = get_local_id(0);
+    const int lp = lx / 24; /* local group id */
+    const int gid = get_group_id(0) * blocks_in_group + lp;/* global group id */
+    const int gidY = gid / img_block_width;
+    const int gidX = gid - gidY * img_block_width;
+
+    const int lidX = lx - lp * 24;
+    const int lidY = get_local_id(1);
+
+    const int cell_x = lidX / 12;
+    const int cell_y = lidY;
+    const int cell_thread_x = lidX - cell_x * 12;
+
+    __local float* hists = smem + lp * cnbins * (CELLS_PER_BLOCK_X * 
+        CELLS_PER_BLOCK_Y * 12 + CELLS_PER_BLOCK_X * CELLS_PER_BLOCK_Y);
+    __local float* final_hist = hists + cnbins * 
+        (CELLS_PER_BLOCK_X * CELLS_PER_BLOCK_Y * 12);
+
+    const int offset_x = gidX * cblock_stride_x + (cell_x << 2) + cell_thread_x;
+    const int offset_y = gidY * cblock_stride_y + (cell_y << 2);
+
+    __global const float* grad_ptr = (gid < blocks_total) ? 
+        grad + offset_y * grad_quadstep + (offset_x << 1) : grad;
+    __global const uchar* qangle_ptr = (gid < blocks_total) ?
+        qangle + offset_y * qangle_step + (offset_x << 1) : qangle;
+
+    __local float* hist = hists + 12 * (cell_y * CELLS_PER_BLOCK_Y + cell_x) + 
+        cell_thread_x;
+    for (int bin_id = 0; bin_id < cnbins; ++bin_id)
+        hist[bin_id * 48] = 0.f;
+
+    const int dist_x = -4 + cell_thread_x - 4 * cell_x;
+    const int dist_center_x = dist_x - 4 * (1 - 2 * cell_x);
+
+    const int dist_y_begin = -4 - 4 * lidY;
+    for (int dist_y = dist_y_begin; dist_y < dist_y_begin + 12; ++dist_y)
+    {
+        float2 vote = (float2) (grad_ptr[0], grad_ptr[1]);
+        uchar2 bin = (uchar2) (qangle_ptr[0], qangle_ptr[1]);
+
+        grad_ptr += grad_quadstep;
+        qangle_ptr += qangle_step;
+
+        int dist_center_y = dist_y - 4 * (1 - 2 * cell_y);
+
+        int idx = (dist_center_y + 8) * 16 + (dist_center_x + 8);
+        float gaussian = gauss_w_lut[idx];
+        idx = (dist_y + 8) * 16 + (dist_x + 8);
+        float interp_weight = gauss_w_lut[256+idx];
+
+        hist[bin.x * 48] += gaussian * interp_weight * vote.x;
+        hist[bin.y * 48] += gaussian * interp_weight * vote.y;
+    }
+    barrier(CLK_LOCAL_MEM_FENCE);
+
+    volatile __local float* hist_ = hist;
+    for (int bin_id = 0; bin_id < cnbins; ++bin_id, hist_ += 48)
+    {
+        if (cell_thread_x < 6)
+            hist_[0] += hist_[6];
+        barrier(CLK_LOCAL_MEM_FENCE);
+        if (cell_thread_x < 3)
+            hist_[0] += hist_[3];
+#ifdef CPU
+        barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+        if (cell_thread_x == 0)
+            final_hist[(cell_x * 2 + cell_y) * cnbins + bin_id] = 
+                hist_[0] + hist_[1] + hist_[2];
+    }
+    barrier(CLK_LOCAL_MEM_FENCE);
+
+    int tid = (cell_y * CELLS_PER_BLOCK_Y + cell_x) * 12 + cell_thread_x;
+    if ((tid < cblock_hist_size) && (gid < blocks_total))
+    {
+        __global float* block_hist = block_hists + 
+            (gidY * img_block_width + gidX) * cblock_hist_size;
+        block_hist[tid] = final_hist[tid];
+    }
+}
+
 //----------------------------------------------------------------------------
 // Histogram computation
 // 12 threads for a cell, 12x4 threads per block
@@ -125,16 +218,14 @@ __kernel void compute_hists_kernel(
         barrier(CLK_LOCAL_MEM_FENCE);
         if (cell_thread_x < 3)
             hist_[0] += hist_[3];
-#ifdef WAVE_SIZE_1
+#ifdef CPU
         barrier(CLK_LOCAL_MEM_FENCE);
 #endif
         if (cell_thread_x == 0)
             final_hist[(cell_x * 2 + cell_y) * cnbins + bin_id] = 
                 hist_[0] + hist_[1] + hist_[2];
     }
-#ifdef WAVE_SIZE_1
     barrier(CLK_LOCAL_MEM_FENCE);
-#endif
 
     int tid = (cell_y * CELLS_PER_BLOCK_Y + cell_x) * 12 + cell_thread_x;
     if ((tid < cblock_hist_size) && (gid < blocks_total))
@@ -145,6 +236,57 @@ __kernel void compute_hists_kernel(
     }
 }
 
+//-------------------------------------------------------------
+//  Normalization of histograms via L2Hys_norm
+//  optimized for the case of 9 bins
+__kernel void normalize_hists_36_kernel(__global float* block_hists, 
+                                        const float threshold, __local float *squares)
+{
+    const int tid = get_local_id(0);
+    const int gid = get_global_id(0);
+    const int bid = tid / 36;      /* block-hist id, (0 - 6) */
+    const int boffset = bid * 36;  /* block-hist offset in the work-group */
+    const int hid = tid - boffset; /* histogram bin id, (0 - 35) */
+
+    float elem = block_hists[gid];
+    squares[tid] = elem * elem;
+    barrier(CLK_LOCAL_MEM_FENCE);
+
+    __local float* smem = squares + boffset;
+    float sum = smem[hid];
+    if (hid < 18)
+        smem[hid] = sum = sum + smem[hid + 18];
+    barrier(CLK_LOCAL_MEM_FENCE);
+    if (hid < 9)
+        smem[hid] = sum = sum + smem[hid + 9];
+    barrier(CLK_LOCAL_MEM_FENCE);
+    if (hid < 4)
+        smem[hid] = sum + smem[hid + 4];
+    barrier(CLK_LOCAL_MEM_FENCE);
+    sum = smem[0] + smem[1] + smem[2] + smem[3] + smem[8];
+
+    elem = elem / (sqrt(sum) + 3.6f);
+    elem = min(elem, threshold);
+
+    barrier(CLK_LOCAL_MEM_FENCE);
+    squares[tid] = elem * elem;
+    barrier(CLK_LOCAL_MEM_FENCE);
+
+    sum = smem[hid];
+    if (hid < 18)
+      smem[hid] = sum = sum + smem[hid + 18];
+    barrier(CLK_LOCAL_MEM_FENCE);
+    if (hid < 9)
+        smem[hid] = sum = sum + smem[hid + 9];
+    barrier(CLK_LOCAL_MEM_FENCE);
+    if (hid < 4)
+        smem[hid] = sum + smem[hid + 4];
+    barrier(CLK_LOCAL_MEM_FENCE);
+    sum = smem[0] + smem[1] + smem[2] + smem[3] + smem[8];
+
+    block_hists[gid] = elem / (sqrt(sum) + 1e-3f);
+}
+
 //-------------------------------------------------------------
 //  Normalization of histograms via L2Hys_norm
 //
@@ -153,76 +295,50 @@ float reduce_smem(volatile __local float* smem, int size)
     unsigned int tid = get_local_id(0);
     float sum = smem[tid];
 
-    if (size >= 512)
-    {
-        if (tid < 256) smem[tid] = sum = sum + smem[tid + 256];
-        barrier(CLK_LOCAL_MEM_FENCE);
-    }
-    if (size >= 256)
-    {
-        if (tid < 128) smem[tid] = sum = sum + smem[tid + 128];
-        barrier(CLK_LOCAL_MEM_FENCE);
-    }
-    if (size >= 128)
-    {
-        if (tid < 64) smem[tid] = sum = sum + smem[tid + 64];
-        barrier(CLK_LOCAL_MEM_FENCE);
-    }
-
+    if (size >= 512) { if (tid < 256) smem[tid] = sum = sum + smem[tid + 256]; 
+        barrier(CLK_LOCAL_MEM_FENCE); }
+    if (size >= 256) { if (tid < 128) smem[tid] = sum = sum + smem[tid + 128]; 
+        barrier(CLK_LOCAL_MEM_FENCE); }
+    if (size >= 128) { if (tid < 64) smem[tid] = sum = sum + smem[tid + 64]; 
+        barrier(CLK_LOCAL_MEM_FENCE); }
+#ifdef CPU
+    if (size >= 64) { if (tid < 32) smem[tid] = sum = sum + smem[tid + 32]; 
+        barrier(CLK_LOCAL_MEM_FENCE); }
+    if (size >= 32) { if (tid < 16) smem[tid] = sum = sum + smem[tid + 16]; 
+        barrier(CLK_LOCAL_MEM_FENCE); }	
+    if (size >= 16) { if (tid < 8) smem[tid] = sum = sum + smem[tid + 8]; 
+        barrier(CLK_LOCAL_MEM_FENCE); }
+    if (size >= 8) { if (tid < 4) smem[tid] = sum = sum + smem[tid + 4]; 
+        barrier(CLK_LOCAL_MEM_FENCE); }
+    if (size >= 4) { if (tid < 2) smem[tid] = sum = sum + smem[tid + 2]; 
+        barrier(CLK_LOCAL_MEM_FENCE); }		
+    if (size >= 2) { if (tid < 1) smem[tid] = sum = sum + smem[tid + 1]; 
+        barrier(CLK_LOCAL_MEM_FENCE); }
+#else
     if (tid < 32)
     {
         if (size >= 64) smem[tid] = sum = sum + smem[tid + 32];
-#if defined(WAVE_SIZE_16) || defined(WAVE_SIZE_1)
-    }
-    barrier(CLK_LOCAL_MEM_FENCE);
-    if (tid < 16)
-    {
-#endif
         if (size >= 32) smem[tid] = sum = sum + smem[tid + 16];
-#ifdef WAVE_SIZE_1
-    }
-    barrier(CLK_LOCAL_MEM_FENCE);
-    if (tid < 8)
-    {
-#endif
         if (size >= 16) smem[tid] = sum = sum + smem[tid + 8];
-#ifdef WAVE_SIZE_1
-    }
-    barrier(CLK_LOCAL_MEM_FENCE);
-    if (tid < 4)
-    {
-#endif
         if (size >= 8) smem[tid] = sum = sum + smem[tid + 4];
-#ifdef WAVE_SIZE_1
-    }
-    barrier(CLK_LOCAL_MEM_FENCE);
-    if (tid < 2)
-    {
-#endif
         if (size >= 4) smem[tid] = sum = sum + smem[tid + 2];
-#ifdef WAVE_SIZE_1
-    }
-    barrier(CLK_LOCAL_MEM_FENCE);
-    if (tid < 1)
-    {
-#endif
         if (size >= 2) smem[tid] = sum = sum + smem[tid + 1];
     }
-
-    barrier(CLK_LOCAL_MEM_FENCE);
-    sum = smem[0];
+#endif
 
     return sum;
 }
 
-__kernel void normalize_hists_kernel(const int nthreads, const int block_hist_size, const int img_block_width,
-                                     __global float* block_hists, const float threshold, __local float *squares)
+__kernel void normalize_hists_kernel(
+    const int nthreads, const int block_hist_size, const int img_block_width,
+    __global float* block_hists, const float threshold, __local float *squares)
 {
     const int tid = get_local_id(0);
     const int gidX = get_group_id(0);
     const int gidY = get_group_id(1);
 
-    __global float* hist = block_hists + (gidY * img_block_width + gidX) * block_hist_size + tid;
+    __global float* hist = block_hists + (gidY * img_block_width + gidX) * 
+        block_hist_size + tid;
 
     float elem = 0.f;
     if (tid < block_hist_size)
@@ -249,100 +365,226 @@ __kernel void normalize_hists_kernel(const int nthreads, const int block_hist_si
 
 //---------------------------------------------------------------------
 //  Linear SVM based classification
-//
-__kernel void classify_hists_kernel(const int cblock_hist_size, const int cdescr_size, const int cdescr_width,
-                                    const int img_win_width, const int img_block_width,
-                                    const int win_block_stride_x, const int win_block_stride_y,
-                                    __global const float * block_hists, __global const float* coefs,
-                                    float free_coef, float threshold, __global uchar* labels)
+//  48x96 window, 9 bins and default parameters
+//  180 threads, each thread corresponds to a bin in a row
+__kernel void classify_hists_180_kernel(
+    const int cdescr_width, const int cdescr_height, const int cblock_hist_size,
+    const int img_win_width, const int img_block_width,
+    const int win_block_stride_x, const int win_block_stride_y,
+    __global const float * block_hists, __global const float* coefs,
+    float free_coef, float threshold, __global uchar* labels)
 {
     const int tid = get_local_id(0);
     const int gidX = get_group_id(0);
     const int gidY = get_group_id(1);
 
-    __global const float* hist = block_hists + (gidY * win_block_stride_y * img_block_width + gidX * win_block_stride_x) * cblock_hist_size;
+    __global const float* hist = block_hists + (gidY * win_block_stride_y * 
+        img_block_width + gidX * win_block_stride_x) * cblock_hist_size;
 
     float product = 0.f;
-    for (int i = tid; i < cdescr_size; i += NTHREADS)
+
+    for (int i = 0; i < cdescr_height; i++)
     {
-        int offset_y = i / cdescr_width;
-        int offset_x = i - offset_y * cdescr_width;
-        product += coefs[i] * hist[offset_y * img_block_width * cblock_hist_size + offset_x];
+        product += coefs[i * cdescr_width + tid] * 
+            hist[i * img_block_width * cblock_hist_size + tid];
     }
 
-    __local float products[NTHREADS];
+    __local float products[180];
 
     products[tid] = product;
 
     barrier(CLK_LOCAL_MEM_FENCE);
 
-    if (tid < 128) products[tid] = product = product + products[tid + 128];
+    if (tid < 90) products[tid] = product = product + products[tid + 90];
     barrier(CLK_LOCAL_MEM_FENCE);
 
-    if (tid < 64) products[tid] = product = product + products[tid + 64];
+    if (tid < 45) products[tid] = product = product + products[tid + 45];
     barrier(CLK_LOCAL_MEM_FENCE);
 
     volatile __local float* smem = products;
-    if (tid < 32)
+#ifdef CPU
+    if (tid < 13) smem[tid] = product = product + smem[tid + 32];
+	barrier(CLK_LOCAL_MEM_FENCE);
+    if (tid < 16) smem[tid] = product = product + smem[tid + 16];
+	barrier(CLK_LOCAL_MEM_FENCE);
+	if(tid<8) smem[tid] = product = product + smem[tid + 8];
+	barrier(CLK_LOCAL_MEM_FENCE);
+	if(tid<4) smem[tid] = product = product + smem[tid + 4];
+	barrier(CLK_LOCAL_MEM_FENCE);
+	if(tid<2) smem[tid] = product = product + smem[tid + 2];
+	barrier(CLK_LOCAL_MEM_FENCE);
+#else
+    if (tid < 13)
     {
         smem[tid] = product = product + smem[tid + 32];
-#if defined(WAVE_SIZE_16) || defined(WAVE_SIZE_1)
     }
-    barrier(CLK_LOCAL_MEM_FENCE);
     if (tid < 16)
     {
-#endif
         smem[tid] = product = product + smem[tid + 16];
-#ifdef WAVE_SIZE_1
-    }
-    barrier(CLK_LOCAL_MEM_FENCE);
-    if (tid < 8)
-    {
-#endif
         smem[tid] = product = product + smem[tid + 8];
-#ifdef WAVE_SIZE_1
+        smem[tid] = product = product + smem[tid + 4];
+        smem[tid] = product = product + smem[tid + 2];
     }
-    barrier(CLK_LOCAL_MEM_FENCE);
-    if (tid < 4)
-    {
 #endif
-        smem[tid] = product = product + smem[tid + 4];
-#ifdef WAVE_SIZE_1
+
+    if (tid == 0){
+		product = product + smem[tid + 1];
+        labels[gidY * img_win_width + gidX] = (product + free_coef >= threshold);
+	}
+}
+
+//---------------------------------------------------------------------
+//  Linear SVM based classification
+//  64x128 window, 9 bins and default parameters
+//  256 threads, 252 of them are used
+__kernel void classify_hists_252_kernel(
+    const int cdescr_width, const int cdescr_height, const int cblock_hist_size,
+    const int img_win_width, const int img_block_width,
+    const int win_block_stride_x, const int win_block_stride_y,
+    __global const float * block_hists, __global const float* coefs,
+    float free_coef, float threshold, __global uchar* labels)
+{
+    const int tid = get_local_id(0);
+    const int gidX = get_group_id(0);
+    const int gidY = get_group_id(1);
+
+    __global const float* hist = block_hists + (gidY * win_block_stride_y * 
+        img_block_width + gidX * win_block_stride_x) * cblock_hist_size;
+
+    float product = 0.f;
+    if (tid < cdescr_width)
+    {
+        for (int i = 0; i < cdescr_height; i++)
+            product += coefs[i * cdescr_width + tid] * 
+                hist[i * img_block_width * cblock_hist_size + tid];
     }
+
+    __local float products[NTHREADS];
+
+    products[tid] = product;
+
     barrier(CLK_LOCAL_MEM_FENCE);
-    if (tid < 2)
-    {
-#endif
+
+    if (tid < 128) products[tid] = product = product + products[tid + 128];
+    barrier(CLK_LOCAL_MEM_FENCE);
+
+    if (tid < 64) products[tid] = product = product + products[tid + 64];
+    barrier(CLK_LOCAL_MEM_FENCE);
+
+	volatile __local float* smem = products;
+#ifdef CPU
+	if(tid<32) smem[tid] = product = product + smem[tid + 32];
+	barrier(CLK_LOCAL_MEM_FENCE);
+	if(tid<16) smem[tid] = product = product + smem[tid + 16];
+	barrier(CLK_LOCAL_MEM_FENCE);
+	if(tid<8) smem[tid] = product = product + smem[tid + 8];
+	barrier(CLK_LOCAL_MEM_FENCE);
+	if(tid<4) smem[tid] = product = product + smem[tid + 4];
+	barrier(CLK_LOCAL_MEM_FENCE);
+	if(tid<2) smem[tid] = product = product + smem[tid + 2];
+	barrier(CLK_LOCAL_MEM_FENCE);
+#else
+    if (tid < 32)
+    {      
+        smem[tid] = product = product + smem[tid + 32];
+        smem[tid] = product = product + smem[tid + 16];
+        smem[tid] = product = product + smem[tid + 8];
+        smem[tid] = product = product + smem[tid + 4];
         smem[tid] = product = product + smem[tid + 2];
-#ifdef WAVE_SIZE_1
     }
-    barrier(CLK_LOCAL_MEM_FENCE);
-    if (tid < 1)
-    {
 #endif
-        smem[tid] = product = product + smem[tid + 1];
+    if (tid == 0){
+		product = product + smem[tid + 1];
+        labels[gidY * img_win_width + gidX] = (product + free_coef >= threshold);
+	}
+}
+
+//---------------------------------------------------------------------
+//  Linear SVM based classification
+//  256 threads
+__kernel void classify_hists_kernel(
+    const int cdescr_size, const int cdescr_width, const int cblock_hist_size,
+    const int img_win_width, const int img_block_width,
+    const int win_block_stride_x, const int win_block_stride_y,
+    __global const float * block_hists, __global const float* coefs,
+    float free_coef, float threshold, __global uchar* labels)
+{
+    const int tid = get_local_id(0);
+    const int gidX = get_group_id(0);
+    const int gidY = get_group_id(1);
+
+    __global const float* hist = block_hists + (gidY * win_block_stride_y * 
+        img_block_width + gidX * win_block_stride_x) * cblock_hist_size;
+
+    float product = 0.f;
+    for (int i = tid; i < cdescr_size; i += NTHREADS)
+    {
+        int offset_y = i / cdescr_width;
+        int offset_x = i - offset_y * cdescr_width;
+        product += coefs[i] * 
+            hist[offset_y * img_block_width * cblock_hist_size + offset_x];
     }
 
-    if (tid == 0)
+    __local float products[NTHREADS];
+
+    products[tid] = product;
+
+    barrier(CLK_LOCAL_MEM_FENCE);
+
+    if (tid < 128) products[tid] = product = product + products[tid + 128];
+    barrier(CLK_LOCAL_MEM_FENCE);
+
+    if (tid < 64) products[tid] = product = product + products[tid + 64];
+    barrier(CLK_LOCAL_MEM_FENCE);
+
+	volatile __local float* smem = products;
+#ifdef CPU
+	if(tid<32) smem[tid] = product = product + smem[tid + 32];
+	barrier(CLK_LOCAL_MEM_FENCE);
+	if(tid<16) smem[tid] = product = product + smem[tid + 16];
+	barrier(CLK_LOCAL_MEM_FENCE);
+	if(tid<8) smem[tid] = product = product + smem[tid + 8];
+	barrier(CLK_LOCAL_MEM_FENCE);
+	if(tid<4) smem[tid] = product = product + smem[tid + 4];
+	barrier(CLK_LOCAL_MEM_FENCE);
+	if(tid<2) smem[tid] = product = product + smem[tid + 2];
+	barrier(CLK_LOCAL_MEM_FENCE);
+#else
+    if (tid < 32)
+    {       
+        smem[tid] = product = product + smem[tid + 32];
+        smem[tid] = product = product + smem[tid + 16];
+        smem[tid] = product = product + smem[tid + 8];
+        smem[tid] = product = product + smem[tid + 4];
+        smem[tid] = product = product + smem[tid + 2];
+    }
+#endif
+    if (tid == 0){
+		smem[tid] = product = product + smem[tid + 1];
         labels[gidY * img_win_width + gidX] = (product + free_coef >= threshold);
+	}
 }
 
 //----------------------------------------------------------------------------
 // Extract descriptors
 
-__kernel void extract_descrs_by_rows_kernel(const int cblock_hist_size, const int descriptors_quadstep, const int cdescr_size, const int cdescr_width,
-        const int img_block_width, const int win_block_stride_x, const int win_block_stride_y,
-        __global const float* block_hists, __global float* descriptors)
+__kernel void extract_descrs_by_rows_kernel(
+    const int cblock_hist_size, const int descriptors_quadstep, 
+    const int cdescr_size, const int cdescr_width, const int img_block_width, 
+    const int win_block_stride_x, const int win_block_stride_y,
+    __global const float* block_hists, __global float* descriptors)
 {
     int tid = get_local_id(0);
     int gidX = get_group_id(0);
     int gidY = get_group_id(1);
 
     // Get left top corner of the window in src
-    __global const float* hist = block_hists + (gidY * win_block_stride_y * img_block_width + gidX * win_block_stride_x) * cblock_hist_size;
+    __global const float* hist = block_hists + (gidY * win_block_stride_y * 
+        img_block_width + gidX * win_block_stride_x) * cblock_hist_size;
 
     // Get left top corner of the window in dst
-    __global float* descriptor = descriptors + (gidY * get_num_groups(0) + gidX) * descriptors_quadstep;
+    __global float* descriptor = descriptors + 
+        (gidY * get_num_groups(0) + gidX) * descriptors_quadstep;
 
     // Copy elements from src to dst
     for (int i = tid; i < cdescr_size; i += NTHREADS)
@@ -353,19 +595,23 @@ __kernel void extract_descrs_by_rows_kernel(const int cblock_hist_size, const in
     }
 }
 
-__kernel void extract_descrs_by_cols_kernel(const int cblock_hist_size, const int descriptors_quadstep, const int cdescr_size,
-        const int cnblocks_win_x, const int cnblocks_win_y, const int img_block_width, const int win_block_stride_x,
-        const int win_block_stride_y, __global const float* block_hists, __global float* descriptors)
+__kernel void extract_descrs_by_cols_kernel(
+    const int cblock_hist_size, const int descriptors_quadstep, const int cdescr_size,
+    const int cnblocks_win_x, const int cnblocks_win_y, const int img_block_width, 
+    const int win_block_stride_x, const int win_block_stride_y, 
+    __global const float* block_hists, __global float* descriptors)
 {
     int tid = get_local_id(0);
     int gidX = get_group_id(0);
     int gidY = get_group_id(1);
 
     // Get left top corner of the window in src
-    __global const float* hist = block_hists + (gidY * win_block_stride_y * img_block_width + gidX * win_block_stride_x) * cblock_hist_size;
+    __global const float* hist = block_hists +  (gidY * win_block_stride_y * 
+        img_block_width + gidX * win_block_stride_x) * cblock_hist_size;
 
     // Get left top corner of the window in dst
-    __global float* descriptor = descriptors + (gidY * get_num_groups(0) + gidX) * descriptors_quadstep;
+    __global float* descriptor = descriptors + 
+        (gidY * get_num_groups(0) + gidX) * descriptors_quadstep;
 
     // Copy elements from src to dst
     for (int i = tid; i < cdescr_size; i += NTHREADS)
@@ -376,16 +622,19 @@ __kernel void extract_descrs_by_cols_kernel(const int cblock_hist_size, const in
         int y = block_idx / cnblocks_win_x;
         int x = block_idx - y * cnblocks_win_x;
 
-        descriptor[(x * cnblocks_win_y + y) * cblock_hist_size + idx_in_block] = hist[(y * img_block_width  + x) * cblock_hist_size + idx_in_block];
+        descriptor[(x * cnblocks_win_y + y) * cblock_hist_size + idx_in_block] = 
+            hist[(y * img_block_width  + x) * cblock_hist_size + idx_in_block];
     }
 }
 
 //----------------------------------------------------------------------------
 // Gradients computation
 
-__kernel void compute_gradients_8UC4_kernel(const int height, const int width, const int img_step, const int grad_quadstep, const int qangle_step,
-        const __global uchar4 * img, __global float * grad, __global uchar * qangle,
-        const float angle_scale, const char correct_gamma, const int cnbins)
+__kernel void compute_gradients_8UC4_kernel(
+    const int height, const int width, 
+    const int img_step, const int grad_quadstep, const int qangle_step,
+    const __global uchar4 * img, __global float * grad, __global uchar * qangle,
+    const float angle_scale, const char correct_gamma, const int cnbins)
 {
     const int x = get_global_id(0);
     const int tid = get_local_id(0);
@@ -426,8 +675,10 @@ __kernel void compute_gradients_8UC4_kernel(const int height, const int width, c
     barrier(CLK_LOCAL_MEM_FENCE);
     if (x < width)
     {
-        float3 a = (float3) (sh_row[tid], sh_row[tid + (NTHREADS + 2)], sh_row[tid + 2 * (NTHREADS + 2)]);
-        float3 b = (float3) (sh_row[tid + 2], sh_row[tid + 2 + (NTHREADS + 2)], sh_row[tid + 2 + 2 * (NTHREADS + 2)]);
+        float3 a = (float3) (sh_row[tid], sh_row[tid + (NTHREADS + 2)], 
+            sh_row[tid + 2 * (NTHREADS + 2)]);
+        float3 b = (float3) (sh_row[tid + 2], sh_row[tid + 2 + (NTHREADS + 2)], 
+            sh_row[tid + 2 + 2 * (NTHREADS + 2)]);
 
         float3 dx;
         if (correct_gamma == 1)
@@ -482,9 +733,11 @@ __kernel void compute_gradients_8UC4_kernel(const int height, const int width, c
     }
 }
 
-__kernel void compute_gradients_8UC1_kernel(const int height, const int width, const int img_step, const int grad_quadstep, const int qangle_step,
-        __global const uchar * img, __global float * grad, __global uchar * qangle,
-        const float angle_scale, const char correct_gamma, const int cnbins)
+__kernel void compute_gradients_8UC1_kernel(
+    const int height, const int width, 
+    const int img_step, const int grad_quadstep, const int qangle_step,
+    __global const uchar * img, __global float * grad, __global uchar * qangle,
+    const float angle_scale, const char correct_gamma, const int cnbins)
 {
     const int x = get_global_id(0);
     const int tid = get_local_id(0);
@@ -539,43 +792,4 @@ __kernel void compute_gradients_8UC1_kernel(const int height, const int width, c
         grad[ (gidY * grad_quadstep + x) << 1 ]       = mag * (1.f - ang);
         grad[ ((gidY * grad_quadstep + x) << 1) + 1 ]   = mag * ang;
     }
-}
-
-//----------------------------------------------------------------------------
-// Resize
-
-__kernel void resize_8UC4_kernel(__global uchar4 * dst, __global const uchar4 * src,
-                                 int dst_offset, int src_offset, int dst_step, int src_step,
-                                 int src_cols, int src_rows, int dst_cols, int dst_rows, float ifx, float ify )
-{
-    int dx = get_global_id(0);
-    int dy = get_global_id(1);
-
-    int sx = (int)floor(dx*ifx+0.5f);
-    int sy = (int)floor(dy*ify+0.5f);
-    sx = min(sx, src_cols-1);
-    sy = min(sy, src_rows-1);
-    int dpos = (dst_offset>>2) + dy * (dst_step>>2) + dx;
-    int spos = (src_offset>>2) + sy * (src_step>>2) + sx;
-
-    if(dx<dst_cols && dy<dst_rows)
-        dst[dpos] = src[spos];
-}
-
-__kernel void resize_8UC1_kernel(__global uchar * dst, __global const uchar * src,
-                                 int dst_offset, int src_offset, int dst_step, int src_step,
-                                 int src_cols, int src_rows, int dst_cols, int dst_rows, float ifx, float ify )
-{
-    int dx = get_global_id(0);
-    int dy = get_global_id(1);
-
-    int sx = (int)floor(dx*ifx+0.5f);
-    int sy = (int)floor(dy*ify+0.5f);
-    sx = min(sx, src_cols-1);
-    sy = min(sy, src_rows-1);
-    int dpos = dst_offset + dy * dst_step + dx;
-    int spos = src_offset + sy * src_step + sx;
-
-    if(dx<dst_cols && dy<dst_rows)
-        dst[dpos] = src[spos];
 }
\ No newline at end of file

From 9ecbce0111324f62221df647d549f441fdb91738 Mon Sep 17 00:00:00 2001
From: peng xiao <hisenxpress@gmail.com>
Date: Wed, 19 Jun 2013 11:31:42 +0800
Subject: [PATCH 17/27] Fix cmake path finding for amd libs. There is no WIN64
 defined in the environment.

---
 cmake/OpenCVDetectOpenCL.cmake | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/cmake/OpenCVDetectOpenCL.cmake b/cmake/OpenCVDetectOpenCL.cmake
index a1e8bbac70..2c96274a8c 100644
--- a/cmake/OpenCVDetectOpenCL.cmake
+++ b/cmake/OpenCVDetectOpenCL.cmake
@@ -44,7 +44,7 @@ if(OPENCL_FOUND)
   set(OPENCL_INCLUDE_DIRS ${OPENCL_INCLUDE_DIR})
   set(OPENCL_LIBRARIES    ${OPENCL_LIBRARY})
 
-  if(WIN64)
+  if(WIN32 AND X86_64)
     set(CLAMD_POSSIBLE_LIB_SUFFIXES lib64/import)
   elseif(WIN32)
     set(CLAMD_POSSIBLE_LIB_SUFFIXES lib32/import)

From 2c198f6cd6802ebfc8d7216f2b06b7c7fb42f6b9 Mon Sep 17 00:00:00 2001
From: yao <bitwangyaoyao@gmail.com>
Date: Wed, 19 Jun 2013 13:03:35 +0800
Subject: [PATCH 18/27] revise accuracy and perf tests

---
 modules/ocl/perf/main.cpp                     |   2 +
 .../perf_calib3d.cpp}                         |  91 ++++----
 modules/ocl/perf/perf_filters.cpp             |  16 +-
 modules/ocl/perf/perf_hog.cpp                 |  76 +------
 modules/ocl/perf/perf_imgproc.cpp             |  46 +++-
 .../{perf_columnsum.cpp => perf_moments.cpp}  |  62 ++---
 modules/ocl/perf/precomp.cpp                  |  14 --
 modules/ocl/test/test_haar.cpp                | 180 ---------------
 modules/ocl/test/test_imgproc.cpp             |  46 +++-
 .../test/{test_hog.cpp => test_objdetect.cpp} | 215 ++++++++++--------
 .../{test_pyrdown.cpp => test_pyramids.cpp}   |  44 +++-
 modules/ocl/test/test_pyrup.cpp               |  91 --------
 modules/ocl/test/utility.cpp                  | 102 ++++-----
 modules/ocl/test/utility.hpp                  |  11 +-
 14 files changed, 387 insertions(+), 609 deletions(-)
 rename modules/ocl/{test/test_columnsum.cpp => perf/perf_calib3d.cpp} (65%)
 rename modules/ocl/perf/{perf_columnsum.cpp => perf_moments.cpp} (68%)
 delete mode 100644 modules/ocl/test/test_haar.cpp
 rename modules/ocl/test/{test_hog.cpp => test_objdetect.cpp} (51%)
 rename modules/ocl/test/{test_pyrdown.cpp => test_pyramids.cpp} (75%)
 delete mode 100644 modules/ocl/test/test_pyrup.cpp

diff --git a/modules/ocl/perf/main.cpp b/modules/ocl/perf/main.cpp
index 2da17755eb..dfcac20bc0 100644
--- a/modules/ocl/perf/main.cpp
+++ b/modules/ocl/perf/main.cpp
@@ -52,6 +52,8 @@ int main(int argc, const char *argv[])
         cerr << "no device found\n";
         return -1;
     }
+    // set this to overwrite binary cache every time the test starts
+    ocl::setBinaryDiskCache(ocl::CACHE_UPDATE);
 
     int devidx = 0;
 
diff --git a/modules/ocl/test/test_columnsum.cpp b/modules/ocl/perf/perf_calib3d.cpp
similarity index 65%
rename from modules/ocl/test/test_columnsum.cpp
rename to modules/ocl/perf/perf_calib3d.cpp
index 231f0657b0..f998ddf0f3 100644
--- a/modules/ocl/test/test_columnsum.cpp
+++ b/modules/ocl/perf/perf_calib3d.cpp
@@ -15,8 +15,8 @@
 // Third party copyrights are property of their respective owners.
 //
 // @Authors
-//	   Chunpeng Zhang chunpeng@multicorewareinc.com
-//
+//    Fangfang Bai, fangfang@multicorewareinc.com
+//    Jin Ma,       jin@multicorewareinc.com
 //
 // Redistribution and use in source and binary forms, with or without modification,
 // are permitted provided that the following conditions are met:
@@ -31,7 +31,7 @@
 //   * The name of the copyright holders may not be used to endorse or promote products
 //     derived from this software without specific prior written permission.
 //
-// This software is provided by the copyright holders and contributors "as is" and
+// This software is provided by the copyright holders and contributors as is and
 // any express or implied warranties, including, but not limited to, the implied
 // warranties of merchantability and fitness for a particular purpose are disclaimed.
 // In no event shall the Intel Corporation or contributors be liable for any direct,
@@ -45,50 +45,57 @@
 //M*/
 
 #include "precomp.hpp"
-#include <iomanip>
+///////////// StereoMatchBM ////////////////////////
+PERFTEST(StereoMatchBM)
+{
+	Mat left_image = imread(abspath("aloeL.jpg"), cv::IMREAD_GRAYSCALE);
+	Mat right_image = imread(abspath("aloeR.jpg"), cv::IMREAD_GRAYSCALE);
+	Mat disp,dst;
+	ocl::oclMat d_left, d_right,d_disp;
+	int n_disp= 128;
+	int winSize =19;
 
-#ifdef HAVE_OPENCL
+	SUBTEST << left_image.cols << 'x' << left_image.rows << "; aloeL.jpg ;"<< right_image.cols << 'x' << right_image.rows << "; aloeR.jpg ";
 
-PARAM_TEST_CASE(ColumnSum, cv::Size)
-{
-    cv::Size size;
-    cv::Mat src;
+	StereoBM bm(0, n_disp, winSize);
+	bm(left_image, right_image, dst);
 
-    virtual void SetUp()
-    {
-        size = GET_PARAM(0);
-    }
-};
+	CPU_ON;
+	bm(left_image, right_image, dst);
+	CPU_OFF;
 
-TEST_P(ColumnSum, Accuracy)
-{
-    cv::Mat src = randomMat(size, CV_32FC1);
-    cv::ocl::oclMat d_dst;
-    cv::ocl::oclMat d_src(src);
-
-    cv::ocl::columnSum(d_src, d_dst);
-
-    cv::Mat dst(d_dst);
-
-    for (int j = 0; j < src.cols; ++j)
-    {
-        float gold = src.at<float>(0, j);
-        float res = dst.at<float>(0, j);
-        ASSERT_NEAR(res, gold, 1e-5);
-    }
-
-    for (int i = 1; i < src.rows; ++i)
-    {
-        for (int j = 0; j < src.cols; ++j)
-        {
-            float gold = src.at<float>(i, j) += src.at<float>(i - 1, j);
-            float res = dst.at<float>(i, j);
-            ASSERT_NEAR(res, gold, 1e-5);
-        }
-    }
+	d_left.upload(left_image);
+	d_right.upload(right_image);
+
+	ocl::StereoBM_OCL d_bm(0, n_disp, winSize);
+
+	WARMUP_ON;
+	d_bm(d_left, d_right, d_disp);
+	WARMUP_OFF;
+
+    cv::Mat ocl_mat;
+    d_disp.download(ocl_mat);
+    ocl_mat.convertTo(ocl_mat, dst.type());
+
+	GPU_ON;
+	d_bm(d_left, d_right, d_disp);
+	GPU_OFF;
+
+	GPU_FULL_ON;
+	d_left.upload(left_image);
+	d_right.upload(right_image);
+	d_bm(d_left, d_right, d_disp);
+	d_disp.download(disp);
+	GPU_FULL_OFF;
+    
+    TestSystem::instance().setAccurate(-1, 0.);
 }
 
-INSTANTIATE_TEST_CASE_P(OCL_ImgProc, ColumnSum, DIFFERENT_SIZES);
 
 
-#endif
+
+
+
+
+
+	
\ No newline at end of file
diff --git a/modules/ocl/perf/perf_filters.cpp b/modules/ocl/perf/perf_filters.cpp
index a05301b34c..e988ce09d6 100644
--- a/modules/ocl/perf/perf_filters.cpp
+++ b/modules/ocl/perf/perf_filters.cpp
@@ -284,6 +284,7 @@ PERFTEST(GaussianBlur)
     Mat src, dst, ocl_dst;
     int all_type[] = {CV_8UC1, CV_8UC4, CV_32FC1, CV_32FC4};
     std::string type_name[] = {"CV_8UC1", "CV_8UC4", "CV_32FC1", "CV_32FC4"};
+    const int ksize = 7;	
 
     for (int size = Min_Size; size <= Max_Size; size *= Multiple)
     {
@@ -291,29 +292,28 @@ PERFTEST(GaussianBlur)
         {
             SUBTEST << size << 'x' << size << "; " << type_name[j] ;
 
-            gen(src, size, size, all_type[j], 5, 16);
+            gen(src, size, size, all_type[j], 0, 256);
 
-            GaussianBlur(src, dst, Size(9, 9), 0);
+            GaussianBlur(src, dst, Size(ksize, ksize), 0);
 
             CPU_ON;
-            GaussianBlur(src, dst, Size(9, 9), 0);
+            GaussianBlur(src, dst, Size(ksize, ksize), 0);
             CPU_OFF;
 
             ocl::oclMat d_src(src);
-            ocl::oclMat d_dst(src.size(), src.type());
-            ocl::oclMat d_buf;
+            ocl::oclMat d_dst;
 
             WARMUP_ON;
-            ocl::GaussianBlur(d_src, d_dst, Size(9, 9), 0);
+            ocl::GaussianBlur(d_src, d_dst, Size(ksize, ksize), 0);
             WARMUP_OFF;
 
             GPU_ON;
-            ocl::GaussianBlur(d_src, d_dst, Size(9, 9), 0);
+            ocl::GaussianBlur(d_src, d_dst, Size(ksize, ksize), 0);
             GPU_OFF;
 
             GPU_FULL_ON;
             d_src.upload(src);
-            ocl::GaussianBlur(d_src, d_dst, Size(9, 9), 0);
+            ocl::GaussianBlur(d_src, d_dst, Size(ksize, ksize), 0);
             d_dst.download(ocl_dst);
             GPU_FULL_OFF;
 
diff --git a/modules/ocl/perf/perf_hog.cpp b/modules/ocl/perf/perf_hog.cpp
index 05093811fe..7daa61396c 100644
--- a/modules/ocl/perf/perf_hog.cpp
+++ b/modules/ocl/perf/perf_hog.cpp
@@ -46,11 +46,6 @@
 #include "precomp.hpp"
 
 ///////////// HOG////////////////////////
-bool match_rect(cv::Rect r1, cv::Rect r2, int threshold)
-{
-    return ((abs(r1.x - r2.x) < threshold) && (abs(r1.y - r2.y) < threshold) &&
-        (abs(r1.width - r2.width) < threshold) && (abs(r1.height - r2.height) < threshold));
-}
 
 PERFTEST(HOG)
 {
@@ -61,13 +56,12 @@ PERFTEST(HOG)
         throw runtime_error("can't open road.png");
     }
 
-
     cv::HOGDescriptor hog;
     hog.setSVMDetector(hog.getDefaultPeopleDetector());
     std::vector<cv::Rect> found_locations;
     std::vector<cv::Rect> d_found_locations;
 
-    SUBTEST << 768 << 'x' << 576 << "; road.png";
+    SUBTEST << src.cols << 'x' << src.rows << "; road.png";
 
     hog.detectMultiScale(src, found_locations);
 
@@ -84,70 +78,10 @@ PERFTEST(HOG)
     ocl_hog.detectMultiScale(d_src, d_found_locations);
     WARMUP_OFF;
     
-    // Ground-truth rectangular people window
-    cv::Rect win1_64x128(231, 190, 72, 144);
-    cv::Rect win2_64x128(621, 156, 97, 194);
-    cv::Rect win1_48x96(238, 198, 63, 126);
-    cv::Rect win2_48x96(619, 161, 92, 185);
-    cv::Rect win3_48x96(488, 136, 56, 112);
-
-    // Compare whether ground-truth windows are detected and compare the number of windows detected.
-    std::vector<int> d_comp(4);
-    std::vector<int> comp(4);
-    for(int i = 0; i < (int)d_comp.size(); i++)
-    {
-        d_comp[i] = 0;
-        comp[i] = 0;
-    }
-
-    int threshold = 10;
-    int val = 32;
-    d_comp[0] = (int)d_found_locations.size();
-    comp[0] = (int)found_locations.size();
-
-    cv::Size winSize = hog.winSize;
-
-    if (winSize == cv::Size(48, 96))
-    {
-        for(int i = 0; i < (int)d_found_locations.size(); i++)
-        {
-            if (match_rect(d_found_locations[i], win1_48x96, threshold))
-                d_comp[1] = val;
-            if (match_rect(d_found_locations[i], win2_48x96, threshold))
-                d_comp[2] = val;
-            if (match_rect(d_found_locations[i], win3_48x96, threshold))
-                d_comp[3] = val;
-        }
-        for(int i = 0; i < (int)found_locations.size(); i++)
-        {
-            if (match_rect(found_locations[i], win1_48x96, threshold))
-                comp[1] = val;
-            if (match_rect(found_locations[i], win2_48x96, threshold))
-                comp[2] = val;
-            if (match_rect(found_locations[i], win3_48x96, threshold))
-                comp[3] = val;
-        }
-    }
-    else if (winSize == cv::Size(64, 128))
-    {
-        for(int i = 0; i < (int)d_found_locations.size(); i++)
-        {
-            if (match_rect(d_found_locations[i], win1_64x128, threshold))
-                d_comp[1] = val;
-            if (match_rect(d_found_locations[i], win2_64x128, threshold))
-                d_comp[2] = val;
-        }
-        for(int i = 0; i < (int)found_locations.size(); i++)
-        {
-            if (match_rect(found_locations[i], win1_64x128, threshold))
-                comp[1] = val;
-            if (match_rect(found_locations[i], win2_64x128, threshold))
-                comp[2] = val;
-        }
-    }
-
-    cv::Mat gpu_rst(d_comp), cpu_rst(comp);
-    TestSystem::instance().ExpectedMatNear(gpu_rst, cpu_rst, 3);
+    if(d_found_locations.size() == found_locations.size())
+        TestSystem::instance().setAccurate(1, 0);
+    else
+        TestSystem::instance().setAccurate(0, abs((int)found_locations.size() - (int)d_found_locations.size()));
 
     GPU_ON;
     ocl_hog.detectMultiScale(d_src, found_locations);
diff --git a/modules/ocl/perf/perf_imgproc.cpp b/modules/ocl/perf/perf_imgproc.cpp
index e87e8213de..b330c5ffae 100644
--- a/modules/ocl/perf/perf_imgproc.cpp
+++ b/modules/ocl/perf/perf_imgproc.cpp
@@ -743,12 +743,12 @@ PERFTEST(meanShiftFiltering)
         WARMUP_OFF;
 
         GPU_ON;
-        ocl::meanShiftFiltering(d_src, d_dst, sp, sr);
+        ocl::meanShiftFiltering(d_src, d_dst, sp, sr, crit);
         GPU_OFF;
 
         GPU_FULL_ON;
         d_src.upload(src);
-        ocl::meanShiftFiltering(d_src, d_dst, sp, sr);
+        ocl::meanShiftFiltering(d_src, d_dst, sp, sr, crit);
         d_dst.download(ocl_dst);
         GPU_FULL_OFF;
 
@@ -969,3 +969,45 @@ PERFTEST(CLAHE)
         }
     }
 }
+
+///////////// columnSum////////////////////////
+PERFTEST(columnSum)
+{
+    Mat src, dst, ocl_dst;
+    ocl::oclMat d_src, d_dst;
+
+    for (int size = Min_Size; size <= Max_Size; size *= Multiple)
+    {
+        SUBTEST << size << 'x' << size << "; CV_32FC1";
+
+        gen(src, size, size, CV_32FC1, 0, 256);
+
+        CPU_ON;
+        dst.create(src.size(), src.type());
+        for (int j = 0; j < src.cols; j++)
+            dst.at<float>(0, j) = src.at<float>(0, j);
+
+        for (int i = 1; i < src.rows; ++i)
+            for (int j = 0; j < src.cols; ++j)
+                dst.at<float>(i, j) = dst.at<float>(i - 1 , j) + src.at<float>(i , j);
+        CPU_OFF;
+
+        d_src.upload(src);
+
+        WARMUP_ON;
+        ocl::columnSum(d_src, d_dst);
+        WARMUP_OFF;
+
+        GPU_ON;
+        ocl::columnSum(d_src, d_dst);
+        GPU_OFF;
+
+        GPU_FULL_ON;
+        d_src.upload(src);
+        ocl::columnSum(d_src, d_dst);
+        d_dst.download(ocl_dst);
+        GPU_FULL_OFF;
+
+        TestSystem::instance().ExpectedMatNear(dst, ocl_dst, 5e-1);
+    }
+}
diff --git a/modules/ocl/perf/perf_columnsum.cpp b/modules/ocl/perf/perf_moments.cpp
similarity index 68%
rename from modules/ocl/perf/perf_columnsum.cpp
rename to modules/ocl/perf/perf_moments.cpp
index ff7ebcd1de..7fa3948dec 100644
--- a/modules/ocl/perf/perf_columnsum.cpp
+++ b/modules/ocl/perf/perf_moments.cpp
@@ -44,45 +44,49 @@
 //
 //M*/
 #include "precomp.hpp"
-
-///////////// columnSum////////////////////////
-PERFTEST(columnSum)
+///////////// Moments ////////////////////////
+PERFTEST(Moments)
 {
-    Mat src, dst, ocl_dst;
-    ocl::oclMat d_src, d_dst;
+    Mat src;
+    bool binaryImage = 0;
+
+    int all_type[] = {CV_8UC1, CV_16SC1, CV_32FC1, CV_64FC1};
+    std::string type_name[] = {"CV_8UC1", "CV_16SC1", "CV_32FC1", "CV_64FC1"};
 
     for (int size = Min_Size; size <= Max_Size; size *= Multiple)
     {
-        SUBTEST << size << 'x' << size << "; CV_32FC1";
+        for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
+        {
+            SUBTEST << size << 'x' << size << "; " << type_name[j];
+
+            gen(src, size, size, all_type[j], 0, 256);
+
+            cv::Moments CvMom = moments(src, binaryImage);
 
-        gen(src, size, size, CV_32FC1, 0, 256);
+            CPU_ON;
+            moments(src, binaryImage);
+            CPU_OFF;
 
-        CPU_ON;
-        dst.create(src.size(), src.type());
-        for (int j = 0; j < src.cols; j++)
-            dst.at<float>(0, j) = src.at<float>(0, j);
+            cv::Moments oclMom;
+            WARMUP_ON;
+            oclMom = ocl::ocl_moments(src, binaryImage);
+            WARMUP_OFF;
 
-        for (int i = 1; i < src.rows; ++i)
-            for (int j = 0; j < src.cols; ++j)
-                dst.at<float>(i, j) = dst.at<float>(i - 1 , j) + src.at<float>(i , j);
-        CPU_OFF;
+            Mat gpu_dst, cpu_dst;
+            HuMoments(CvMom, cpu_dst);
+            HuMoments(oclMom, gpu_dst);
 
-        d_src.upload(src);
+            GPU_ON;
+            ocl::ocl_moments(src, binaryImage);
+            GPU_OFF;
 
-        WARMUP_ON;
-        ocl::columnSum(d_src, d_dst);
-        WARMUP_OFF;
+            GPU_FULL_ON;
+            ocl::ocl_moments(src, binaryImage);
+            GPU_FULL_OFF;
 
-        GPU_ON;
-        ocl::columnSum(d_src, d_dst);
-        GPU_OFF;
+            TestSystem::instance().ExpectedMatNear(gpu_dst, cpu_dst, .5);
 
-        GPU_FULL_ON;
-        d_src.upload(src);
-        ocl::columnSum(d_src, d_dst);
-        d_dst.download(ocl_dst);
-        GPU_FULL_OFF;
+        }
 
-        TestSystem::instance().ExpectedMatNear(dst, ocl_dst, 5e-1);
     }
-}
\ No newline at end of file
+}
diff --git a/modules/ocl/perf/precomp.cpp b/modules/ocl/perf/precomp.cpp
index 71a13a1ee2..9fc634290e 100644
--- a/modules/ocl/perf/precomp.cpp
+++ b/modules/ocl/perf/precomp.cpp
@@ -331,20 +331,6 @@ void TestSystem::printMetrics(int is_accurate, double cpu_time, double gpu_time,
     cout << setiosflags(ios_base::left);
     stringstream stream;
 
-#if 0
-    if(is_accurate == 1)
-            stream << "Pass";
-    else if(is_accurate_ == 0)
-            stream << "Fail";
-    else if(is_accurate == -1)
-        stream << " ";
-    else
-    {
-        std::cout<<"is_accurate errer: "<<is_accurate<<"\n";
-        exit(-1);
-    }
-#endif
-
     std::stringstream &cur_subtest_description = getCurSubtestDescription();
    
 #if GTEST_OS_WINDOWS&&!GTEST_OS_WINDOWS_MOBILE
diff --git a/modules/ocl/test/test_haar.cpp b/modules/ocl/test/test_haar.cpp
deleted file mode 100644
index 52ddbb7c6a..0000000000
--- a/modules/ocl/test/test_haar.cpp
+++ /dev/null
@@ -1,180 +0,0 @@
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-//  By downloading, copying, installing or using the software you agree to this license.
-//  If you do not agree to this license, do not download, install,
-//  copy or use the software.
-//
-//
-//                           License Agreement
-//                For Open Source Computer Vision Library
-//
-// Copyright (C) 2010-2012, Institute Of Software Chinese Academy Of Science, all rights reserved.
-// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
-// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// @Authors
-//    Jia Haipeng, jiahaipeng95@gmail.com
-//    Sen Liu, swjutls1987@126.com
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-//   * Redistribution's of source code must retain the above copyright notice,
-//     this list of conditions and the following disclaimer.
-//
-//   * Redistribution's in binary form must reproduce the above copyright notice,
-//     this list of conditions and the following disclaimer in the documentation
-//     and/or other oclMaterials provided with the distribution.
-//
-//   * The name of the copyright holders may not be used to endorse or promote products
-//     derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "opencv2/objdetect/objdetect.hpp"
-#include "precomp.hpp"
-
-#ifdef HAVE_OPENCL
-
-using namespace cvtest;
-using namespace testing;
-using namespace std;
-using namespace cv;
-extern string workdir;
-
-namespace
-{
-IMPLEMENT_PARAM_CLASS(CascadeName, std::string);
-CascadeName cascade_frontalface_alt(std::string("haarcascade_frontalface_alt.xml"));
-CascadeName cascade_frontalface_alt2(std::string("haarcascade_frontalface_alt2.xml"));
-struct getRect
-{
-    Rect operator ()(const CvAvgComp &e) const
-    {
-        return e.rect;
-    }
-};
-}
-
-PARAM_TEST_CASE(Haar, double, int, CascadeName)
-{
-    cv::ocl::OclCascadeClassifier cascade, nestedCascade;
-    cv::CascadeClassifier cpucascade, cpunestedCascade;
-
-    double scale;
-    int flags;
-    std::string cascadeName;
-
-    virtual void SetUp()
-    {
-        scale = GET_PARAM(0);
-        flags = GET_PARAM(1);
-        cascadeName = (workdir + "../../data/haarcascades/").append(GET_PARAM(2));
-
-        if( (!cascade.load( cascadeName )) || (!cpucascade.load(cascadeName)) )
-        {
-            cout << "ERROR: Could not load classifier cascade" << endl;
-            return;
-        }
-    }
-};
-
-////////////////////////////////faceDetect/////////////////////////////////////////////////
-TEST_P(Haar, FaceDetect)
-{
-    string imgName = workdir + "lena.jpg";
-    Mat img = imread( imgName, 1 );
-
-    if(img.empty())
-    {
-        std::cout << "Couldn't read " << imgName << std::endl;
-        return ;
-    }
-
-    vector<Rect> faces, oclfaces;
-
-    Mat gray, smallImg(cvRound (img.rows / scale), cvRound(img.cols / scale), CV_8UC1 );
-    MemStorage storage(cvCreateMemStorage(0));
-    cvtColor( img, gray, CV_BGR2GRAY );
-    resize( gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR );
-    equalizeHist( smallImg, smallImg );
-
-    cv::ocl::oclMat image;
-    CvSeq *_objects;
-    image.upload(smallImg);
-    _objects = cascade.oclHaarDetectObjects( image, storage, 1.1,
-                   3, flags, Size(30, 30), Size(0, 0) );
-    vector<CvAvgComp> vecAvgComp;
-    Seq<CvAvgComp>(_objects).copyTo(vecAvgComp);
-    oclfaces.resize(vecAvgComp.size());
-    std::transform(vecAvgComp.begin(), vecAvgComp.end(), oclfaces.begin(), getRect());
-    
-    cpucascade.detectMultiScale( smallImg, faces,  1.1, 3,
-                                 flags,
-                                 Size(30, 30), Size(0, 0) );
-    EXPECT_EQ(faces.size(), oclfaces.size());
-}
-
-TEST_P(Haar, FaceDetectUseBuf)
-{
-    string imgName = workdir + "lena.jpg";
-    Mat img = imread( imgName, 1 );
-
-    if(img.empty())
-    {
-        std::cout << "Couldn't read " << imgName << std::endl;
-        return ;
-    }
-
-    vector<Rect> faces, oclfaces;
-
-    Mat gray, smallImg(cvRound (img.rows / scale), cvRound(img.cols / scale), CV_8UC1 );
-    cvtColor( img, gray, CV_BGR2GRAY );
-    resize( gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR );
-    equalizeHist( smallImg, smallImg );
-
-    cv::ocl::oclMat image;
-    image.upload(smallImg);
-
-    cv::ocl::OclCascadeClassifierBuf cascadebuf;
-    if( !cascadebuf.load( cascadeName ) )
-    {
-        cout << "ERROR: Could not load classifier cascade for FaceDetectUseBuf!" << endl;
-        return;
-    }
-    cascadebuf.detectMultiScale( image, oclfaces,  1.1, 3,
-                                 flags,
-                                 Size(30, 30), Size(0, 0) );
-
-    cpucascade.detectMultiScale( smallImg, faces,  1.1, 3,
-                                 flags,
-                                 Size(30, 30), Size(0, 0) );
-    EXPECT_EQ(faces.size(), oclfaces.size());
-
-    // intentionally run ocl facedetect again and check if it still works after the first run
-    cascadebuf.detectMultiScale( image, oclfaces,  1.1, 3,
-        flags,
-        Size(30, 30));
-    cascadebuf.release();
-    EXPECT_EQ(faces.size(), oclfaces.size());
-}
-
-INSTANTIATE_TEST_CASE_P(FaceDetect, Haar,
-    Combine(Values(1.0),
-            Values(CV_HAAR_SCALE_IMAGE, 0), Values(cascade_frontalface_alt, cascade_frontalface_alt2)));
-
-#endif // HAVE_OPENCL
diff --git a/modules/ocl/test/test_imgproc.cpp b/modules/ocl/test/test_imgproc.cpp
index b9f4740b17..3a98671d51 100644
--- a/modules/ocl/test/test_imgproc.cpp
+++ b/modules/ocl/test/test_imgproc.cpp
@@ -1573,6 +1573,47 @@ TEST_P(Convolve, Mat)
     }
 }
 
+//////////////////////////////// ColumnSum //////////////////////////////////////
+PARAM_TEST_CASE(ColumnSum, cv::Size)
+{
+    cv::Size size;
+    cv::Mat src;
+
+    virtual void SetUp()
+    {
+        size = GET_PARAM(0);
+    }
+};
+
+TEST_P(ColumnSum, Accuracy)
+{
+    cv::Mat src = randomMat(size, CV_32FC1);
+    cv::ocl::oclMat d_dst;
+    cv::ocl::oclMat d_src(src);
+
+    cv::ocl::columnSum(d_src, d_dst);
+
+    cv::Mat dst(d_dst);
+
+    for (int j = 0; j < src.cols; ++j)
+    {
+        float gold = src.at<float>(0, j);
+        float res = dst.at<float>(0, j);
+        ASSERT_NEAR(res, gold, 1e-5);
+    }
+
+    for (int i = 1; i < src.rows; ++i)
+    {
+        for (int j = 0; j < src.cols; ++j)
+        {
+            float gold = src.at<float>(i, j) += src.at<float>(i - 1, j);
+            float res = dst.at<float>(i, j);
+            ASSERT_NEAR(res, gold, 1e-5);
+        }
+    }
+}
+/////////////////////////////////////////////////////////////////////////////////////
+
 INSTANTIATE_TEST_CASE_P(ImgprocTestBase, equalizeHist, Combine(
                             ONE_TYPE(CV_8UC1),
                             NULL_TYPE,
@@ -1688,7 +1729,6 @@ INSTANTIATE_TEST_CASE_P(ImgProc, CLAHE, Combine(
                         Values(cv::Size(128, 128), cv::Size(113, 113), cv::Size(1300, 1300)),
                         Values(0.0, 40.0)));
 
-//INSTANTIATE_TEST_CASE_P(ConvolveTestBase, Convolve, Combine(
-//                            Values(CV_32FC1, CV_32FC1),
-//                            Values(false))); // Values(false) is the reserved parameter
+INSTANTIATE_TEST_CASE_P(OCL_ImgProc, ColumnSum, DIFFERENT_SIZES);
+
 #endif // HAVE_OPENCL
diff --git a/modules/ocl/test/test_hog.cpp b/modules/ocl/test/test_objdetect.cpp
similarity index 51%
rename from modules/ocl/test/test_hog.cpp
rename to modules/ocl/test/test_objdetect.cpp
index cfc4e3963f..86590f7981 100644
--- a/modules/ocl/test/test_hog.cpp
+++ b/modules/ocl/test/test_objdetect.cpp
@@ -15,7 +15,7 @@
 // Third party copyrights are property of their respective owners.
 //
 // @Authors
-//		Wenju He, wenju@multicorewareinc.com
+//		Yao Wang, bitwangyaoyao@gmail.com
 //
 // Redistribution and use in source and binary forms, with or without modification,
 // are permitted provided that the following conditions are met:
@@ -45,51 +45,58 @@
 
 #include "precomp.hpp"
 #include "opencv2/core/core.hpp"
-using namespace std;
+#include "opencv2/objdetect/objdetect.hpp"
+
+using namespace cv;
+using namespace testing;
 #ifdef HAVE_OPENCL
 
 extern string workdir;
-PARAM_TEST_CASE(HOG, cv::Size, int)
+
+///////////////////// HOG /////////////////////////////
+PARAM_TEST_CASE(HOG, Size, int)
 {
-    cv::Size winSize;
+    Size winSize;
     int type;
+    Mat img_rgb;
     virtual void SetUp()
     {
         winSize = GET_PARAM(0);
         type = GET_PARAM(1);
+        img_rgb = readImage(workdir + "../gpu/road.png");
+        if(img_rgb.empty())
+        {
+            std::cout << "Couldn't read road.png" << std::endl;
+        }
     }
 };
 
 TEST_P(HOG, GetDescriptors)
 {
-    // Load image
-    cv::Mat img_rgb = readImage(workdir + "lena.jpg");
-    ASSERT_FALSE(img_rgb.empty());
-
     // Convert image
-    cv::Mat img;
+    Mat img;
     switch (type)
     {
     case CV_8UC1:
-        cv::cvtColor(img_rgb, img, CV_BGR2GRAY);
+        cvtColor(img_rgb, img, CV_BGR2GRAY);
         break;
     case CV_8UC4:
     default:
-        cv::cvtColor(img_rgb, img, CV_BGR2BGRA);
+        cvtColor(img_rgb, img, CV_BGR2BGRA);
         break;
     }
-    cv::ocl::oclMat d_img(img);
+    ocl::oclMat d_img(img);
 
     // HOGs
-    cv::ocl::HOGDescriptor ocl_hog;
+    ocl::HOGDescriptor ocl_hog;
     ocl_hog.gamma_correction = true;
-    cv::HOGDescriptor hog;
+    HOGDescriptor hog;
     hog.gammaCorrection = true;
 
     // Compute descriptor
-    cv::ocl::oclMat d_descriptors;
+    ocl::oclMat d_descriptors;
     ocl_hog.getDescriptors(d_img, ocl_hog.win_size, d_descriptors, ocl_hog.DESCR_FORMAT_COL_BY_COL);
-    cv::Mat down_descriptors;
+    Mat down_descriptors;
     d_descriptors.download(down_descriptors);
     down_descriptors = down_descriptors.reshape(0, down_descriptors.cols * down_descriptors.rows);
 
@@ -105,45 +112,34 @@ TEST_P(HOG, GetDescriptors)
         hog.compute(img_rgb, descriptors, ocl_hog.win_size);
         break;
     }
-    cv::Mat cpu_descriptors(descriptors);
+    Mat cpu_descriptors(descriptors);
 
     EXPECT_MAT_SIMILAR(down_descriptors, cpu_descriptors, 1e-2);
 }
 
-
-bool match_rect(cv::Rect r1, cv::Rect r2, int threshold)
-{
-    return ((abs(r1.x - r2.x) < threshold) && (abs(r1.y - r2.y) < threshold) &&
-            (abs(r1.width - r2.width) < threshold) && (abs(r1.height - r2.height) < threshold));
-}
-
 TEST_P(HOG, Detect)
 {
-    // Load image
-    cv::Mat img_rgb = readImage(workdir + "lena.jpg");
-    ASSERT_FALSE(img_rgb.empty());
-
     // Convert image
-    cv::Mat img;
+    Mat img;
     switch (type)
     {
     case CV_8UC1:
-        cv::cvtColor(img_rgb, img, CV_BGR2GRAY);
+        cvtColor(img_rgb, img, CV_BGR2GRAY);
         break;
     case CV_8UC4:
     default:
-        cv::cvtColor(img_rgb, img, CV_BGR2BGRA);
+        cvtColor(img_rgb, img, CV_BGR2BGRA);
         break;
     }
-    cv::ocl::oclMat d_img(img);
+    ocl::oclMat d_img(img);
 
     // HOGs
-    if ((winSize != cv::Size(48, 96)) && (winSize != cv::Size(64, 128)))
-        winSize = cv::Size(64, 128);
-    cv::ocl::HOGDescriptor ocl_hog(winSize);
+    if ((winSize != Size(48, 96)) && (winSize != Size(64, 128)))
+        winSize = Size(64, 128);
+    ocl::HOGDescriptor ocl_hog(winSize);
     ocl_hog.gamma_correction = true;
 
-    cv::HOGDescriptor hog;
+    HOGDescriptor hog;
     hog.winSize = winSize;
     hog.gammaCorrection = true;
 
@@ -165,88 +161,117 @@ TEST_P(HOG, Detect)
     }
 
     // OpenCL detection
-    std::vector<cv::Rect> d_found;
-    ocl_hog.detectMultiScale(d_img, d_found, 0, cv::Size(8, 8), cv::Size(0, 0), 1.05, 2);
+    std::vector<Rect> d_found;
+    ocl_hog.detectMultiScale(d_img, d_found, 0, Size(8, 8), Size(0, 0), 1.05, 6);
 
     // CPU detection
-    std::vector<cv::Rect> found;
+    std::vector<Rect> found;
     switch (type)
     {
     case CV_8UC1:
-        hog.detectMultiScale(img, found, 0, cv::Size(8, 8), cv::Size(0, 0), 1.05, 2);
+        hog.detectMultiScale(img, found, 0, Size(8, 8), Size(0, 0), 1.05, 6);
         break;
     case CV_8UC4:
     default:
-        hog.detectMultiScale(img_rgb, found, 0, cv::Size(8, 8), cv::Size(0, 0), 1.05, 2);
+        hog.detectMultiScale(img_rgb, found, 0, Size(8, 8), Size(0, 0), 1.05, 6);
         break;
     }
 
-    // Ground-truth rectangular people window
-    cv::Rect win1_64x128(231, 190, 72, 144);
-    cv::Rect win2_64x128(621, 156, 97, 194);
-    cv::Rect win1_48x96(238, 198, 63, 126);
-    cv::Rect win2_48x96(619, 161, 92, 185);
-    cv::Rect win3_48x96(488, 136, 56, 112);
-
-    // Compare whether ground-truth windows are detected and compare the number of windows detected.
-    std::vector<int> d_comp(4);
-    std::vector<int> comp(4);
-    for(int i = 0; i < (int)d_comp.size(); i++)
-    {
-        d_comp[i] = 0;
-        comp[i] = 0;
-    }
+    EXPECT_LT(checkRectSimilarity(img.size(), found, d_found), 1.0);
+}
 
-    int threshold = 10;
-    int val = 32;
-    d_comp[0] = (int)d_found.size();
-    comp[0] = (int)found.size();
-    if (winSize == cv::Size(48, 96))
+
+INSTANTIATE_TEST_CASE_P(OCL_ObjDetect, HOG, testing::Combine(
+                            testing::Values(Size(64, 128), Size(48, 96)),
+                            testing::Values(MatType(CV_8UC1), MatType(CV_8UC4))));
+
+///////////////////////////// Haar //////////////////////////////
+IMPLEMENT_PARAM_CLASS(CascadeName, std::string);
+CascadeName cascade_frontalface_alt(std::string("haarcascade_frontalface_alt.xml"));
+CascadeName cascade_frontalface_alt2(std::string("haarcascade_frontalface_alt2.xml"));
+struct getRect
+{
+    Rect operator ()(const CvAvgComp &e) const
     {
-        for(int i = 0; i < (int)d_found.size(); i++)
-        {
-            if (match_rect(d_found[i], win1_48x96, threshold))
-                d_comp[1] = val;
-            if (match_rect(d_found[i], win2_48x96, threshold))
-                d_comp[2] = val;
-            if (match_rect(d_found[i], win3_48x96, threshold))
-                d_comp[3] = val;
-        }
-        for(int i = 0; i < (int)found.size(); i++)
-        {
-            if (match_rect(found[i], win1_48x96, threshold))
-                comp[1] = val;
-            if (match_rect(found[i], win2_48x96, threshold))
-                comp[2] = val;
-            if (match_rect(found[i], win3_48x96, threshold))
-                comp[3] = val;
-        }
+        return e.rect;
     }
-    else if (winSize == cv::Size(64, 128))
+};
+
+PARAM_TEST_CASE(Haar, int, CascadeName)
+{
+    ocl::OclCascadeClassifier cascade, nestedCascade;
+    CascadeClassifier cpucascade, cpunestedCascade;
+
+    int flags;
+    std::string cascadeName;
+    vector<Rect> faces, oclfaces;
+    Mat img;
+    ocl::oclMat d_img;
+
+    virtual void SetUp()
     {
-        for(int i = 0; i < (int)d_found.size(); i++)
+        flags = GET_PARAM(0);
+        cascadeName = (workdir + "../../data/haarcascades/").append(GET_PARAM(1));
+        if( (!cascade.load( cascadeName )) || (!cpucascade.load(cascadeName)) )
         {
-            if (match_rect(d_found[i], win1_64x128, threshold))
-                d_comp[1] = val;
-            if (match_rect(d_found[i], win2_64x128, threshold))
-                d_comp[2] = val;
+            std::cout << "ERROR: Could not load classifier cascade" << std::endl;
+            return;
         }
-        for(int i = 0; i < (int)found.size(); i++)
+        img = readImage(workdir + "lena.jpg", IMREAD_GRAYSCALE);
+        if(img.empty())
         {
-            if (match_rect(found[i], win1_64x128, threshold))
-                comp[1] = val;
-            if (match_rect(found[i], win2_64x128, threshold))
-                comp[2] = val;
+            std::cout << "Couldn't read lena.jpg" << std::endl;
+            return ;
         }
+        equalizeHist(img, img);
+        d_img.upload(img);
     }
+};
 
-    EXPECT_MAT_NEAR(cv::Mat(d_comp), cv::Mat(comp), 3);
+TEST_P(Haar, FaceDetect)
+{
+    MemStorage storage(cvCreateMemStorage(0));
+    CvSeq *_objects;
+    _objects = cascade.oclHaarDetectObjects(d_img, storage, 1.1, 3, 
+                                            flags, Size(30, 30), Size(0, 0));
+    vector<CvAvgComp> vecAvgComp;
+    Seq<CvAvgComp>(_objects).copyTo(vecAvgComp);
+    oclfaces.resize(vecAvgComp.size());
+    std::transform(vecAvgComp.begin(), vecAvgComp.end(), oclfaces.begin(), getRect());
+    
+    cpucascade.detectMultiScale(img, faces,  1.1, 3,
+                                flags,
+                                Size(30, 30), Size(0, 0));
+
+    EXPECT_LT(checkRectSimilarity(img.size(), faces, oclfaces), 1.0);
 }
 
+TEST_P(Haar, FaceDetectUseBuf)
+{
+    ocl::OclCascadeClassifierBuf cascadebuf;
+    if(!cascadebuf.load(cascadeName))
+    {
+        std::cout << "ERROR: Could not load classifier cascade for FaceDetectUseBuf!" << std::endl;
+        return;
+    }
+    cascadebuf.detectMultiScale(d_img, oclfaces,  1.1, 3,
+                                flags,
+                                Size(30, 30), Size(0, 0));
+    cpucascade.detectMultiScale(img, faces,  1.1, 3,
+                                flags,
+                                Size(30, 30), Size(0, 0));
 
-INSTANTIATE_TEST_CASE_P(OCL_ObjDetect, HOG, testing::Combine(
-                            testing::Values(cv::Size(64, 128), cv::Size(48, 96)),
-                            testing::Values(MatType(CV_8UC1), MatType(CV_8UC4))));
+    // intentionally run ocl facedetect again and check if it still works after the first run
+    cascadebuf.detectMultiScale(d_img, oclfaces,  1.1, 3,
+                                flags,
+                                Size(30, 30));
+    cascadebuf.release();
+
+    EXPECT_LT(checkRectSimilarity(img.size(), faces, oclfaces), 1.0);
+}
 
+INSTANTIATE_TEST_CASE_P(OCL_ObjDetect, Haar,
+    Combine(Values(CV_HAAR_SCALE_IMAGE, 0), 
+            Values(cascade_frontalface_alt/*, cascade_frontalface_alt2*/)));
 
-#endif //HAVE_OPENCL
+#endif //HAVE_OPENCL
\ No newline at end of file
diff --git a/modules/ocl/test/test_pyrdown.cpp b/modules/ocl/test/test_pyramids.cpp
similarity index 75%
rename from modules/ocl/test/test_pyrdown.cpp
rename to modules/ocl/test/test_pyramids.cpp
index 6d00fb5e45..1bd188dea6 100644
--- a/modules/ocl/test/test_pyrdown.cpp
+++ b/modules/ocl/test/test_pyramids.cpp
@@ -15,7 +15,6 @@
 // Third party copyrights are property of their respective owners.
 //
 // @Authors
-//    Dachuan Zhao, dachuan@multicorewareinc.com
 //    Yao Wang yao@multicorewareinc.com
 //
 // Redistribution and use in source and binary forms, with or without modification,
@@ -56,11 +55,12 @@ using namespace cvtest;
 using namespace testing;
 using namespace std;
 
-PARAM_TEST_CASE(PyrDown, MatType, int)
+PARAM_TEST_CASE(PyrBase, MatType, int)
 {
     int type;
     int channels;
-
+    Mat dst_cpu;
+    oclMat gdst;
     virtual void SetUp()
     {
         type = GET_PARAM(0);
@@ -69,19 +69,19 @@ PARAM_TEST_CASE(PyrDown, MatType, int)
 
 };
 
+/////////////////////// PyrDown //////////////////////////
+struct PyrDown : PyrBase {};
 
 TEST_P(PyrDown, Mat)
 {
     for(int j = 0; j < LOOP_TIMES; j++)
     {
-        cv::Size size(MWIDTH, MHEIGHT);
-        cv::RNG &rng = TS::ptr()->get_rng();
-        cv::Mat src = randomMat(rng, size, CV_MAKETYPE(type, channels), 0, 100, false);
-
-        cv::ocl::oclMat gsrc(src), gdst;
-        cv::Mat dst_cpu;
-        cv::pyrDown(src, dst_cpu);
-        cv::ocl::pyrDown(gsrc, gdst);
+        Size size(MWIDTH, MHEIGHT);
+        Mat src = randomMat(size, CV_MAKETYPE(type, channels));
+        oclMat gsrc(src);
+        
+        pyrDown(src, dst_cpu);
+        pyrDown(gsrc, gdst);
 
         EXPECT_MAT_NEAR(dst_cpu, Mat(gdst), type == CV_32F ? 1e-4f : 1.0f);
     }
@@ -90,5 +90,27 @@ TEST_P(PyrDown, Mat)
 INSTANTIATE_TEST_CASE_P(OCL_ImgProc, PyrDown, Combine(
                             Values(CV_8U, CV_32F), Values(1, 3, 4)));
 
+/////////////////////// PyrUp //////////////////////////
+
+struct PyrUp : PyrBase {};
+
+TEST_P(PyrUp, Accuracy)
+{
+    for(int j = 0; j < LOOP_TIMES; j++)
+    {
+        Size size(MWIDTH, MHEIGHT);
+        Mat src = randomMat(size, CV_MAKETYPE(type, channels));
+        oclMat gsrc(src);
+
+        pyrUp(src, dst_cpu);
+        pyrUp(gsrc, gdst);
+
+        EXPECT_MAT_NEAR(dst_cpu, Mat(gdst), (type == CV_32F ? 1e-4f : 1.0));
+    }
 
+}
+
+
+INSTANTIATE_TEST_CASE_P(OCL_ImgProc, PyrUp, testing::Combine(
+                            Values(CV_8U, CV_32F), Values(1, 3, 4)));
 #endif // HAVE_OPENCL
diff --git a/modules/ocl/test/test_pyrup.cpp b/modules/ocl/test/test_pyrup.cpp
deleted file mode 100644
index afd3e8b1b8..0000000000
--- a/modules/ocl/test/test_pyrup.cpp
+++ /dev/null
@@ -1,91 +0,0 @@
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-//  By downloading, copying, installing or using the software you agree to this license.
-//  If you do not agree to this license, do not download, install,
-//  copy or use the software.
-//
-//
-//                           License Agreement
-//                For Open Source Computer Vision Library
-//
-// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
-// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// @Authors
-//    Zhang Chunpeng chunpeng@multicorewareinc.com
-//    Yao Wang yao@multicorewareinc.com
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-//   * Redistribution's of source code must retain the above copyright notice,
-//     this list of conditions and the following disclaimer.
-//
-//   * Redistribution's in binary form must reproduce the above copyright notice,
-//     this list of conditions and the following disclaimer in the documentation
-//     and/or other oclMaterials provided with the distribution.
-//
-//   * The name of the copyright holders may not be used to endorse or promote products
-//     derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "precomp.hpp"
-#include "opencv2/core/core.hpp"
-
-#ifdef HAVE_OPENCL
-
-using namespace cv;
-using namespace cvtest;
-using namespace testing;
-using namespace std;
-
-PARAM_TEST_CASE(PyrUp, MatType, int)
-{
-    int type;
-    int channels;
-
-    virtual void SetUp()
-    {
-        type = GET_PARAM(0);
-        channels = GET_PARAM(1);
-    }
-};
-
-TEST_P(PyrUp, Accuracy)
-{
-    for(int j = 0; j < LOOP_TIMES; j++)
-    {
-        Size size(MWIDTH, MHEIGHT);
-        Mat src = randomMat(size, CV_MAKETYPE(type, channels));
-        Mat dst_gold;
-        pyrUp(src, dst_gold);
-        ocl::oclMat dst;
-        ocl::oclMat srcMat(src);
-        ocl::pyrUp(srcMat, dst);
-
-        EXPECT_MAT_NEAR(dst_gold, Mat(dst), (type == CV_32F ? 1e-4f : 1.0));
-    }
-
-}
-
-
-INSTANTIATE_TEST_CASE_P(OCL_ImgProc, PyrUp, testing::Combine(
-                            Values(CV_8U, CV_32F), Values(1, 3, 4)));
-
-
-#endif // HAVE_OPENCL
\ No newline at end of file
diff --git a/modules/ocl/test/utility.cpp b/modules/ocl/test/utility.cpp
index 4b21081a8b..27f9cec079 100644
--- a/modules/ocl/test/utility.cpp
+++ b/modules/ocl/test/utility.cpp
@@ -100,12 +100,6 @@ Mat randomMat(Size size, int type, double minVal, double maxVal)
     return randomMat(TS::ptr()->get_rng(), size, type, minVal, maxVal, false);
 }
 
-
-
-
-
-
-
 /*
 void showDiff(InputArray gold_, InputArray actual_, double eps)
 {
@@ -137,58 +131,7 @@ void showDiff(InputArray gold_, InputArray actual_, double eps)
 }
 */
 
-/*
-bool supportFeature(const DeviceInfo& info, FeatureSet feature)
-{
-    return TargetArchs::builtWith(feature) && info.supports(feature);
-}
-
-const vector<DeviceInfo>& devices()
-{
-    static vector<DeviceInfo> devs;
-    static bool first = true;
-
-    if (first)
-    {
-        int deviceCount = getCudaEnabledDeviceCount();
-
-        devs.reserve(deviceCount);
-
-        for (int i = 0; i < deviceCount; ++i)
-        {
-            DeviceInfo info(i);
-            if (info.isCompatible())
-                devs.push_back(info);
-        }
-
-        first = false;
-    }
-
-    return devs;
-}
 
-vector<DeviceInfo> devices(FeatureSet feature)
-{
-    const vector<DeviceInfo>& d = devices();
-
-    vector<DeviceInfo> devs_filtered;
-
-    if (TargetArchs::builtWith(feature))
-    {
-        devs_filtered.reserve(d.size());
-
-        for (size_t i = 0, size = d.size(); i < size; ++i)
-        {
-            const DeviceInfo& info = d[i];
-
-            if (info.supports(feature))
-                devs_filtered.push_back(info);
-        }
-    }
-
-    return devs_filtered;
-}
-*/
 
 vector<MatType> types(int depth_start, int depth_end, int cn_start, int cn_end)
 {
@@ -264,3 +207,48 @@ void PrintTo(const Inverse &inverse, std::ostream *os)
         (*os) << "direct";
 }
 
+double checkRectSimilarity(Size sz, std::vector<Rect>& ob1, std::vector<Rect>& ob2)
+{
+    double final_test_result = 0.0;
+    size_t sz1 = ob1.size();
+    size_t sz2 = ob2.size();
+
+    if(sz1 != sz2)
+    {
+        return sz1 > sz2 ? (double)(sz1 - sz2) : (double)(sz2 - sz1);
+    }
+    else
+    {
+        if(sz1==0 && sz2==0)
+            return 0;
+        cv::Mat cpu_result(sz, CV_8UC1);
+        cpu_result.setTo(0);
+
+        for(vector<Rect>::const_iterator r = ob1.begin(); r != ob1.end(); r++)
+        {      
+            cv::Mat cpu_result_roi(cpu_result, *r);
+            cpu_result_roi.setTo(1);
+            cpu_result.copyTo(cpu_result);
+        }
+        int cpu_area = cv::countNonZero(cpu_result > 0);
+
+        cv::Mat gpu_result(sz, CV_8UC1);
+        gpu_result.setTo(0);
+        for(vector<Rect>::const_iterator r2 = ob2.begin(); r2 != ob2.end(); r2++)
+        {
+            cv::Mat gpu_result_roi(gpu_result, *r2);
+            gpu_result_roi.setTo(1);
+            gpu_result.copyTo(gpu_result);
+        }
+
+        cv::Mat result_;
+        multiply(cpu_result, gpu_result, result_);
+        int result = cv::countNonZero(result_ > 0);
+        if(cpu_area!=0 && result!=0)
+            final_test_result = 1.0 - (double)result/(double)cpu_area;
+        else if(cpu_area==0 && result!=0)
+            final_test_result = -1;
+    }
+    return final_test_result;
+}
+
diff --git a/modules/ocl/test/utility.hpp b/modules/ocl/test/utility.hpp
index 42fa69384d..0b101ec50b 100644
--- a/modules/ocl/test/utility.hpp
+++ b/modules/ocl/test/utility.hpp
@@ -55,13 +55,12 @@ cv::Mat randomMat(cv::Size size, int type, double minVal = 0.0, double maxVal =
 
 void showDiff(cv::InputArray gold, cv::InputArray actual, double eps);
 
-//! return true if device supports specified feature and gpu module was built with support the feature.
-//bool supportFeature(const cv::gpu::DeviceInfo& info, cv::gpu::FeatureSet feature);
+// This function test if gpu_rst matches cpu_rst.
+// If the two vectors are not equal, it will return the difference in vector size
+// Else it will return (total diff of each cpu and gpu rects covered pixels)/(total cpu rects covered pixels)
+// The smaller, the better matched
+double checkRectSimilarity(cv::Size sz, std::vector<cv::Rect>& ob1, std::vector<cv::Rect>& ob2);
 
-//! return all devices compatible with current gpu module build.
-//const std::vector<cv::ocl::DeviceInfo>& devices();
-//! return all devices compatible with current gpu module build which support specified feature.
-//std::vector<cv::ocl::DeviceInfo> devices(cv::gpu::FeatureSet feature);
 
 //! read image from testdata folder.
 cv::Mat readImage(const std::string &fileName, int flags = cv::IMREAD_COLOR);

From f1c549fabf2d916df306a889137de49f3ef338d5 Mon Sep 17 00:00:00 2001
From: yao <bitwangyaoyao@gmail.com>
Date: Wed, 19 Jun 2013 16:36:23 +0800
Subject: [PATCH 19/27] revise ocl samples, add tvl1 sample

---
 samples/ocl/facedetect.cpp         | 159 ++++++++------
 samples/ocl/hog.cpp                | 333 +++++++++++------------------
 samples/ocl/pyrlk_optical_flow.cpp |  59 +++--
 samples/ocl/squares.cpp            | 232 ++++++++++++++++----
 samples/ocl/stereo_match.cpp       | 306 ++++++++++++--------------
 samples/ocl/surf_matcher.cpp       | 205 +++++++-----------
 samples/ocl/tvl1_optical_flow.cpp  | 265 +++++++++++++++++++++++
 7 files changed, 919 insertions(+), 640 deletions(-)
 create mode 100644 samples/ocl/tvl1_optical_flow.cpp

diff --git a/samples/ocl/facedetect.cpp b/samples/ocl/facedetect.cpp
index 684c2d923b..a49610aeb7 100644
--- a/samples/ocl/facedetect.cpp
+++ b/samples/ocl/facedetect.cpp
@@ -7,55 +7,67 @@
 
 using namespace std;
 using namespace cv;
-#define LOOP_NUM 10 
+#define LOOP_NUM 10
 
 const static Scalar colors[] =  { CV_RGB(0,0,255),
-        CV_RGB(0,128,255),
-        CV_RGB(0,255,255),
-        CV_RGB(0,255,0),
-        CV_RGB(255,128,0),
-        CV_RGB(255,255,0),
-        CV_RGB(255,0,0),
-        CV_RGB(255,0,255)} ;
+                                  CV_RGB(0,128,255),
+                                  CV_RGB(0,255,255),
+                                  CV_RGB(0,255,0),
+                                  CV_RGB(255,128,0),
+                                  CV_RGB(255,255,0),
+                                  CV_RGB(255,0,0),
+                                  CV_RGB(255,0,255)
+                                } ;
+
 
 int64 work_begin = 0;
 int64 work_end = 0;
+string outputName;
 
-static void workBegin() 
-{ 
+static void workBegin()
+{
     work_begin = getTickCount();
 }
 static void workEnd()
 {
     work_end += (getTickCount() - work_begin);
 }
-static double getTime(){
+static double getTime()
+{
     return work_end /((double)cvGetTickFrequency() * 1000.);
 }
 
-void detect( Mat& img, vector<Rect>& faces, 
-    cv::ocl::OclCascadeClassifierBuf& cascade, 
-    double scale, bool calTime);
 
-void detectCPU( Mat& img, vector<Rect>& faces, 
-    CascadeClassifier& cascade, 
-    double scale, bool calTime);
+void detect( Mat& img, vector<Rect>& faces,
+             ocl::OclCascadeClassifierBuf& cascade,
+             double scale, bool calTime);
+
+
+void detectCPU( Mat& img, vector<Rect>& faces,
+                CascadeClassifier& cascade,
+                double scale, bool calTime);
+
 
 void Draw(Mat& img, vector<Rect>& faces, double scale);
 
+
 // This function test if gpu_rst matches cpu_rst.
 // If the two vectors are not equal, it will return the difference in vector size
 // Else if will return (total diff of each cpu and gpu rects covered pixels)/(total cpu rects covered pixels)
-double checkRectSimilarity(Size sz, std::vector<Rect>& cpu_rst, std::vector<Rect>& gpu_rst);
+double checkRectSimilarity(Size sz, vector<Rect>& cpu_rst, vector<Rect>& gpu_rst);
+
 
 int main( int argc, const char** argv )
 {
     const char* keys =
         "{ h | help       | false       | print help message }"
         "{ i | input      |             | specify input image }"
-        "{ t | template   | ../../../data/haarcascades/haarcascade_frontalface_alt.xml  | specify template file }"
+        "{ t | template   | haarcascade_frontalface_alt.xml |"
+        " specify template file path }"
         "{ c | scale      |   1.0       | scale image }"
-        "{ s | use_cpu    | false       | use cpu or gpu to process the image }";
+        "{ s | use_cpu    | false       | use cpu or gpu to process the image }"
+        "{ o | output     | facedetect_output.jpg  |"
+        " specify output image save path(only works when input is images) }";
 
     CommandLineParser cmd(argc, argv, keys);
     if (cmd.get<bool>("help"))
@@ -69,9 +81,10 @@ int main( int argc, const char** argv )
 
     bool useCPU = cmd.get<bool>("s");
     string inputName = cmd.get<string>("i");
+    outputName = cmd.get<string>("o");
     string cascadeName = cmd.get<string>("t");
     double scale = cmd.get<double>("c");
-    cv::ocl::OclCascadeClassifierBuf cascade;
+    ocl::OclCascadeClassifierBuf cascade;
     CascadeClassifier  cpu_cascade;
 
     if( !cascade.load( cascadeName ) || !cpu_cascade.load(cascadeName) )
@@ -83,7 +96,7 @@ int main( int argc, const char** argv )
     if( inputName.empty() )
     {
         capture = cvCaptureFromCAM(0);
-        if(!capture) 
+        if(!capture)
             cout << "Capture from CAM 0 didn't work" << endl;
     }
     else if( inputName.size() )
@@ -92,7 +105,7 @@ int main( int argc, const char** argv )
         if( image.empty() )
         {
             capture = cvCaptureFromAVI( inputName.c_str() );
-            if(!capture) 
+            if(!capture)
                 cout << "Capture from AVI didn't work" << endl;
             return -1;
         }
@@ -100,14 +113,15 @@ int main( int argc, const char** argv )
     else
     {
         image = imread( "lena.jpg", 1 );
-        if(image.empty()) 
+        if(image.empty())
             cout << "Couldn't read lena.jpg" << endl;
         return -1;
     }
 
+
     cvNamedWindow( "result", 1 );
-    std::vector<cv::ocl::Info> oclinfo;
-    int devnums = cv::ocl::getDevice(oclinfo);
+    vector<ocl::Info> oclinfo;
+    int devnums = ocl::getDevice(oclinfo);
     if( devnums < 1 )
     {
         std::cout << "no device found\n";
@@ -130,19 +144,23 @@ int main( int argc, const char** argv )
                 frame.copyTo( frameCopy );
             else
                 flip( frame, frameCopy, 0 );
-            if(useCPU){
+            if(useCPU)
+            {
                 detectCPU(frameCopy, faces, cpu_cascade, scale, false);
             }
-            else{
-                detect(frameCopy, faces, cascade, scale, false);     
+            else
+            {
+                detect(frameCopy, faces, cascade, scale, false);
             }
             Draw(frameCopy, faces, scale);
             if( waitKey( 10 ) >= 0 )
                 goto _cleanup_;
         }
 
+
         waitKey(0);
 
+
 _cleanup_:
         cvReleaseCapture( &capture );
     }
@@ -152,18 +170,21 @@ _cleanup_:
         vector<Rect> faces;
         vector<Rect> ref_rst;
         double accuracy = 0.;
-        for(int i = 0; i <= LOOP_NUM;i ++) 
+        for(int i = 0; i <= LOOP_NUM; i ++)
         {
             cout << "loop" << i << endl;
-            if(useCPU){
-                detectCPU(image, faces, cpu_cascade, scale, i==0?false:true);  
+            if(useCPU)
+            {
+                detectCPU(image, faces, cpu_cascade, scale, i==0?false:true);
             }
-            else{
+            else
+            {
                 detect(image, faces, cascade, scale, i==0?false:true);
-                if(i == 0){
+                if(i == 0)
+                {
                     detectCPU(image, ref_rst, cpu_cascade, scale, false);
                     accuracy = checkRectSimilarity(image.size(), ref_rst, faces);
-                }                    
+                }
             }
             if (i == LOOP_NUM)
             {
@@ -180,31 +201,31 @@ _cleanup_:
     }
 
     cvDestroyWindow("result");
-
     return 0;
 }
 
-void detect( Mat& img, vector<Rect>& faces, 
-    cv::ocl::OclCascadeClassifierBuf& cascade, 
-    double scale, bool calTime)
+void detect( Mat& img, vector<Rect>& faces,
+             ocl::OclCascadeClassifierBuf& cascade,
+             double scale, bool calTime)
 {
-    cv::ocl::oclMat image(img);
-    cv::ocl::oclMat gray, smallImg( cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 );
+    ocl::oclMat image(img);
+    ocl::oclMat gray, smallImg( cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 );
     if(calTime) workBegin();
-    cv::ocl::cvtColor( image, gray, CV_BGR2GRAY );
-    cv::ocl::resize( gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR );
-    cv::ocl::equalizeHist( smallImg, smallImg );
+    ocl::cvtColor( image, gray, CV_BGR2GRAY );
+    ocl::resize( gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR );
+    ocl::equalizeHist( smallImg, smallImg );
 
     cascade.detectMultiScale( smallImg, faces, 1.1,
-        3, 0
-        |CV_HAAR_SCALE_IMAGE
-        , Size(30,30), Size(0, 0) );
+                              3, 0
+                              |CV_HAAR_SCALE_IMAGE
+                              , Size(30,30), Size(0, 0) );
     if(calTime) workEnd();
 }
 
-void detectCPU( Mat& img, vector<Rect>& faces, 
-    CascadeClassifier& cascade, 
-    double scale, bool calTime)
+
+void detectCPU( Mat& img, vector<Rect>& faces,
+                CascadeClassifier& cascade,
+                double scale, bool calTime)
 {
     if(calTime) workBegin();
     Mat cpu_gray, cpu_smallImg( cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 );
@@ -212,11 +233,12 @@ void detectCPU( Mat& img, vector<Rect>& faces,
     resize(cpu_gray, cpu_smallImg, cpu_smallImg.size(), 0, 0, INTER_LINEAR);
     equalizeHist(cpu_smallImg, cpu_smallImg);
     cascade.detectMultiScale(cpu_smallImg, faces, 1.1,
-        3, 0 | CV_HAAR_SCALE_IMAGE,
-        Size(30, 30), Size(0, 0));
-    if(calTime) workEnd(); 
+                             3, 0 | CV_HAAR_SCALE_IMAGE,
+                             Size(30, 30), Size(0, 0));
+    if(calTime) workEnd();
 }
 
+
 void Draw(Mat& img, vector<Rect>& faces, double scale)
 {
     int i = 0;
@@ -230,31 +252,38 @@ void Draw(Mat& img, vector<Rect>& faces, double scale)
         radius = cvRound((r->width + r->height)*0.25*scale);
         circle( img, center, radius, color, 3, 8, 0 );
     }
-    cv::imshow( "result", img );
+    imshow( "result", img );
+    imwrite( outputName, img );
 }
 
-double checkRectSimilarity(Size sz, std::vector<Rect>& ob1, std::vector<Rect>& ob2)
+
+double checkRectSimilarity(Size sz, vector<Rect>& ob1, vector<Rect>& ob2)
 {
     double final_test_result = 0.0;
     size_t sz1 = ob1.size();
     size_t sz2 = ob2.size();
 
     if(sz1 != sz2)
+    {
         return sz1 > sz2 ? (double)(sz1 - sz2) : (double)(sz2 - sz1);
+    }
     else
     {
-        cv::Mat cpu_result(sz, CV_8UC1);
+        if(sz1==0 && sz2==0)
+            return 0;
+        Mat cpu_result(sz, CV_8UC1);
         cpu_result.setTo(0);
 
         for(vector<Rect>::const_iterator r = ob1.begin(); r != ob1.end(); r++)
-        {      
-            cv::Mat cpu_result_roi(cpu_result, *r);
+        {
+            Mat cpu_result_roi(cpu_result, *r);
             cpu_result_roi.setTo(1);
             cpu_result.copyTo(cpu_result);
         }
-        int cpu_area = cv::countNonZero(cpu_result > 0);
+        int cpu_area = countNonZero(cpu_result > 0);
+
 
-        cv::Mat gpu_result(sz, CV_8UC1);
+        Mat gpu_result(sz, CV_8UC1);
         gpu_result.setTo(0);
         for(vector<Rect>::const_iterator r2 = ob2.begin(); r2 != ob2.end(); r2++)
         {
@@ -263,11 +292,13 @@ double checkRectSimilarity(Size sz, std::vector<Rect>& ob1, std::vector<Rect>& o
             gpu_result.copyTo(gpu_result);
         }
 
-        cv::Mat result_;
+        Mat result_;
         multiply(cpu_result, gpu_result, result_);
-        int result = cv::countNonZero(result_ > 0);
-
-        final_test_result = 1.0 - (double)result/(double)cpu_area;
+        int result = countNonZero(result_ > 0);
+        if(cpu_area!=0 && result!=0)
+            final_test_result = 1.0 - (double)result/(double)cpu_area;
+        else if(cpu_area==0 && result!=0)
+            final_test_result = -1;
     }
     return final_test_result;
 }
diff --git a/samples/ocl/hog.cpp b/samples/ocl/hog.cpp
index 28be6fa9af..ff53e010cf 100644
--- a/samples/ocl/hog.cpp
+++ b/samples/ocl/hog.cpp
@@ -10,75 +10,39 @@
 using namespace std;
 using namespace cv;
 
-bool help_showed = false;
-
-class Args
-{
-public:
-    Args();
-    static Args read(int argc, char** argv);
-
-    string src;
-    bool src_is_video;
-    bool src_is_camera;
-    int camera_id;
-
-    bool write_video;
-    string dst_video;
-    double dst_video_fps;
-
-    bool make_gray;
-
-    bool resize_src;
-    int width, height;
-
-    double scale;
-    int nlevels;
-    int gr_threshold;
-
-    double hit_threshold;
-    bool hit_threshold_auto;
-
-    int win_width;
-    int win_stride_width, win_stride_height;
-
-    bool gamma_corr;
-};
-
 class App
 {
 public:
-    App(const Args& s);
+    App(CommandLineParser& cmd);
     void run();
-
     void handleKey(char key);
-
     void hogWorkBegin();
     void hogWorkEnd();
     string hogWorkFps() const;
-
     void workBegin();
     void workEnd();
     string workFps() const;
-
     string message() const;
 
+
 // This function test if gpu_rst matches cpu_rst.
 // If the two vectors are not equal, it will return the difference in vector size
-// Else if will return 
+// Else if will return
 // (total diff of each cpu and gpu rects covered pixels)/(total cpu rects covered pixels)
-    double checkRectSimilarity(Size sz, 
-                               std::vector<Rect>& cpu_rst, 
+    double checkRectSimilarity(Size sz,
+                               std::vector<Rect>& cpu_rst,
                                std::vector<Rect>& gpu_rst);
 private:
     App operator=(App&);
 
-    Args args;
+    //Args args;
     bool running;
-
     bool use_gpu;
     bool make_gray;
     double scale;
+    double resize_scale;
+    int win_width;
+    int win_stride_width, win_stride_height;
     int gr_threshold;
     int nlevels;
     double hit_threshold;
@@ -86,119 +50,49 @@ private:
 
     int64 hog_work_begin;
     double hog_work_fps;
-
     int64 work_begin;
     double work_fps;
-};
 
-static void printHelp()
-{
-    cout << "Histogram of Oriented Gradients descriptor and detector sample.\n"
-         << "\nUsage: hog_gpu\n"
-         << "  (<image>|--video <vide>|--camera <camera_id>) # frames source\n"
-         << "  [--make_gray <true/false>] # convert image to gray one or not\n"
-         << "  [--resize_src <true/false>] # do resize of the source image or not\n"
-         << "  [--width <int>] # resized image width\n"
-         << "  [--height <int>] # resized image height\n"
-         << "  [--hit_threshold <double>] # classifying plane distance threshold (0.0 usually)\n"
-         << "  [--scale <double>] # HOG window scale factor\n"
-         << "  [--nlevels <int>] # max number of HOG window scales\n"
-         << "  [--win_width <int>] # width of the window (48 or 64)\n"
-         << "  [--win_stride_width <int>] # distance by OX axis between neighbour wins\n"
-         << "  [--win_stride_height <int>] # distance by OY axis between neighbour wins\n"
-         << "  [--gr_threshold <int>] # merging similar rects constant\n"
-         << "  [--gamma_correct <int>] # do gamma correction or not\n"
-         << "  [--write_video <bool>] # write video or not\n"
-         << "  [--dst_video <path>] # output video path\n"
-         << "  [--dst_video_fps <double>] # output video fps\n";
-    help_showed = true;
-}
+    string img_source;
+    string vdo_source;
+    string output;
+    int camera_id;
+};
 
 int main(int argc, char** argv)
 {
+    const char* keys =
+        "{ h |  help    | false          | print help message }"
+        "{ i |  input   |                | specify input image}"
+        "{ c | camera   | -1             | enable camera capturing }"
+        "{ v | video    |                | use video as input }"
+        "{ g |  gray    | false          | convert image to gray one or not}"
+        "{ s |  scale   | 1.0            | resize the image before detect}"
+        "{ l |larger_win| false          | use 64x128 window}"
+        "{ o |  output  |                | specify output path when input is images}";
+    CommandLineParser cmd(argc, argv, keys);
+    App app(cmd);
     try
     {
-        if (argc < 2)
-            printHelp();
-        Args args = Args::read(argc, argv);
-        if (help_showed)
-            return -1;
-        App app(args);
         app.run();
     }
-    catch (const Exception& e) { return cout << "error: "  << e.what() << endl, 1; }
-    catch (const exception& e) { return cout << "error: "  << e.what() << endl, 1; }
-    catch(...) { return cout << "unknown exception" << endl, 1; }
-    return 0;
-}
-
-
-Args::Args()
-{
-    src_is_video = false;
-    src_is_camera = false;
-    camera_id = 0;
-
-    write_video = false;
-    dst_video_fps = 24.;
-
-    make_gray = false;
-
-    resize_src = false;
-    width = 640;
-    height = 480;
-
-    scale = 1.05;
-    nlevels = 13;
-    gr_threshold = 8;
-    hit_threshold = 1.4;
-    hit_threshold_auto = true;
-
-    win_width = 48;
-    win_stride_width = 8;
-    win_stride_height = 8;
-
-    gamma_corr = true;
-}
-
-
-Args Args::read(int argc, char** argv)
-{
-    Args args;
-    for (int i = 1; i < argc; i++)
+    catch (const Exception& e)
     {
-        if (string(argv[i]) == "--make_gray") args.make_gray = (string(argv[++i]) == "true");
-        else if (string(argv[i]) == "--resize_src") args.resize_src = (string(argv[++i]) == "true");
-        else if (string(argv[i]) == "--width") args.width = atoi(argv[++i]);
-        else if (string(argv[i]) == "--height") args.height = atoi(argv[++i]);
-        else if (string(argv[i]) == "--hit_threshold")
-        {
-            args.hit_threshold = atof(argv[++i]);
-            args.hit_threshold_auto = false;
-        }
-        else if (string(argv[i]) == "--scale") args.scale = atof(argv[++i]);
-        else if (string(argv[i]) == "--nlevels") args.nlevels = atoi(argv[++i]);
-        else if (string(argv[i]) == "--win_width") args.win_width = atoi(argv[++i]);
-        else if (string(argv[i]) == "--win_stride_width") args.win_stride_width = atoi(argv[++i]);
-        else if (string(argv[i]) == "--win_stride_height") args.win_stride_height = atoi(argv[++i]);
-        else if (string(argv[i]) == "--gr_threshold") args.gr_threshold = atoi(argv[++i]);
-        else if (string(argv[i]) == "--gamma_correct") args.gamma_corr = (string(argv[++i]) == "true");
-        else if (string(argv[i]) == "--write_video") args.write_video = (string(argv[++i]) == "true");
-        else if (string(argv[i]) == "--dst_video") args.dst_video = argv[++i];
-        else if (string(argv[i]) == "--dst_video_fps") args.dst_video_fps = atof(argv[++i]);
-        else if (string(argv[i]) == "--help") printHelp();
-        else if (string(argv[i]) == "--video") { args.src = argv[++i]; args.src_is_video = true; }
-        else if (string(argv[i]) == "--camera") { args.camera_id = atoi(argv[++i]); args.src_is_camera = true; }
-        else if (args.src.empty()) args.src = argv[i];
-        else throw runtime_error((string("unknown key: ") + argv[i]));
+        return cout << "error: "  << e.what() << endl, 1;
+    }
+    catch (const exception& e)
+    {
+        return cout << "error: "  << e.what() << endl, 1;
     }
-    return args;
+    catch(...)
+    {
+        return cout << "unknown exception" << endl, 1;
+    }
+    return 0;
 }
 
-
-App::App(const Args& s)
+App::App(CommandLineParser& cmd)
 {
-    args = s;
     cout << "\nControls:\n"
          << "\tESC - exit\n"
          << "\tm - change mode GPU <-> CPU\n"
@@ -209,56 +103,56 @@ App::App(const Args& s)
          << "\t4/r - increase/decrease hit threshold\n"
          << endl;
 
-    use_gpu = true;
-    make_gray = args.make_gray;
-    scale = args.scale;
-    gr_threshold = args.gr_threshold;
-    nlevels = args.nlevels;
-
-    if (args.hit_threshold_auto)
-        args.hit_threshold = args.win_width == 48 ? 1.4 : 0.;
-    hit_threshold = args.hit_threshold;
 
-    gamma_corr = args.gamma_corr;
+    use_gpu = true;
+    make_gray = cmd.get<bool>("g");
+    resize_scale = cmd.get<double>("s");
+    win_width = cmd.get<bool>("l") == true ? 64 : 48;
+    vdo_source = cmd.get<string>("v");
+    img_source = cmd.get<string>("i");
+    output = cmd.get<string>("o");
+    camera_id = cmd.get<int>("c");
 
-    if (args.win_width != 64 && args.win_width != 48)
-        args.win_width = 64;
+    win_stride_width = 8;
+    win_stride_height = 8;
+    gr_threshold = 8;
+    nlevels = 13;
+    hit_threshold = win_width == 48 ? 1.4 : 0.;
+    scale = 1.05;
+    gamma_corr = true;
 
-    cout << "Scale: " << scale << endl;
-    if (args.resize_src)
-        cout << "Resized source: (" << args.width << ", " << args.height << ")\n";
     cout << "Group threshold: " << gr_threshold << endl;
     cout << "Levels number: " << nlevels << endl;
-    cout << "Win width: " << args.win_width << endl;
-    cout << "Win stride: (" << args.win_stride_width << ", " << args.win_stride_height << ")\n";
+    cout << "Win width: " << win_width << endl;
+    cout << "Win stride: (" << win_stride_width << ", " << win_stride_height << ")\n";
     cout << "Hit threshold: " << hit_threshold << endl;
     cout << "Gamma correction: " << gamma_corr << endl;
     cout << endl;
 }
 
-
 void App::run()
 {
-    std::vector<ocl::Info> oclinfo;
+    vector<ocl::Info> oclinfo;
     ocl::getDevice(oclinfo);
     running = true;
-    cv::VideoWriter video_writer;
+    VideoWriter video_writer;
 
-    Size win_size(args.win_width, args.win_width * 2); //(64, 128) or (48, 96)
-    Size win_stride(args.win_stride_width, args.win_stride_height);
+    Size win_size(win_width, win_width * 2);
+    Size win_stride(win_stride_width, win_stride_height);
 
     // Create HOG descriptors and detectors here
     vector<float> detector;
     if (win_size == Size(64, 128))
-        detector = cv::ocl::HOGDescriptor::getPeopleDetector64x128();
+        detector = ocl::HOGDescriptor::getPeopleDetector64x128();
     else
-        detector = cv::ocl::HOGDescriptor::getPeopleDetector48x96();
+        detector = ocl::HOGDescriptor::getPeopleDetector48x96();
+
 
-    cv::ocl::HOGDescriptor gpu_hog(win_size, Size(16, 16), Size(8, 8), Size(8, 8), 9,
-                                   cv::ocl::HOGDescriptor::DEFAULT_WIN_SIGMA, 0.2, gamma_corr,
-                                   cv::ocl::HOGDescriptor::DEFAULT_NLEVELS);
-    cv::HOGDescriptor cpu_hog(win_size, Size(16, 16), Size(8, 8), Size(8, 8), 9, 1, -1,
-                              HOGDescriptor::L2Hys, 0.2, gamma_corr, cv::HOGDescriptor::DEFAULT_NLEVELS);
+    ocl::HOGDescriptor gpu_hog(win_size, Size(16, 16), Size(8, 8), Size(8, 8), 9,
+                               ocl::HOGDescriptor::DEFAULT_WIN_SIGMA, 0.2, gamma_corr,
+                               ocl::HOGDescriptor::DEFAULT_NLEVELS);
+    HOGDescriptor cpu_hog(win_size, Size(16, 16), Size(8, 8), Size(8, 8), 9, 1, -1,
+                          HOGDescriptor::L2Hys, 0.2, gamma_corr, cv::HOGDescriptor::DEFAULT_NLEVELS);
     gpu_hog.setSVMDetector(detector);
     cpu_hog.setSVMDetector(detector);
 
@@ -267,29 +161,29 @@ void App::run()
         VideoCapture vc;
         Mat frame;
 
-        if (args.src_is_video)
+        if (vdo_source!="")
         {
-            vc.open(args.src.c_str());
+            vc.open(vdo_source.c_str());
             if (!vc.isOpened())
-                throw runtime_error(string("can't open video file: " + args.src));
+                throw runtime_error(string("can't open video file: " + vdo_source));
             vc >> frame;
         }
-        else if (args.src_is_camera)
+        else if (camera_id != -1)
         {
-            vc.open(args.camera_id);
+            vc.open(camera_id);
             if (!vc.isOpened())
             {
                 stringstream msg;
-                msg << "can't open camera: " << args.camera_id;
+                msg << "can't open camera: " << camera_id;
                 throw runtime_error(msg.str());
             }
             vc >> frame;
         }
         else
         {
-            frame = imread(args.src);
+            frame = imread(img_source);
             if (frame.empty())
-                throw runtime_error(string("can't open image file: " + args.src));
+                throw runtime_error(string("can't open image file: " + img_source));
         }
 
         Mat img_aux, img, img_to_show;
@@ -307,13 +201,15 @@ void App::run()
             else frame.copyTo(img_aux);
 
             // Resize image
-            if (args.resize_src) resize(img_aux, img, Size(args.width, args.height));
+            if (abs(scale-1.0)>0.001)
+            {
+                Size sz((int)((double)img_aux.cols/resize_scale), (int)((double)img_aux.rows/resize_scale));
+                resize(img_aux, img, sz);
+            }
             else img = img_aux;
             img_to_show = img;
-
             gpu_hog.nlevels = nlevels;
             cpu_hog.nlevels = nlevels;
-
             vector<Rect> found;
 
             // Perform HOG classification
@@ -330,15 +226,16 @@ void App::run()
                     vector<Rect> ref_rst;
                     cvtColor(img, img, CV_BGRA2BGR);
                     cpu_hog.detectMultiScale(img, ref_rst, hit_threshold, win_stride,
-                                              Size(0, 0), scale, gr_threshold-2);
+                                             Size(0, 0), scale, gr_threshold-2);
                     double accuracy = checkRectSimilarity(img.size(), ref_rst, found);
-                    cout << "\naccuracy value: " << accuracy << endl;           
-                } 
-           }
+                    cout << "\naccuracy value: " << accuracy << endl;
+                }
+            }
             else cpu_hog.detectMultiScale(img, found, hit_threshold, win_stride,
-                                          Size(0, 0), scale, gr_threshold);
+                                              Size(0, 0), scale, gr_threshold);
             hogWorkEnd();
 
+
             // Draw positive classified windows
             for (size_t i = 0; i < found.size(); i++)
             {
@@ -353,25 +250,31 @@ void App::run()
             putText(img_to_show, "FPS (HOG only): " + hogWorkFps(), Point(5, 65), FONT_HERSHEY_SIMPLEX, 1., Scalar(255, 100, 0), 2);
             putText(img_to_show, "FPS (total): " + workFps(), Point(5, 105), FONT_HERSHEY_SIMPLEX, 1., Scalar(255, 100, 0), 2);
             imshow("opencv_gpu_hog", img_to_show);
-
-            if (args.src_is_video || args.src_is_camera) vc >> frame;
+            if (vdo_source!="" || camera_id!=-1) vc >> frame;
 
             workEnd();
 
-            if (args.write_video)
+            if (output!="")
             {
-                if (!video_writer.isOpened())
+                if (img_source!="")     // wirte image
                 {
-                    video_writer.open(args.dst_video, CV_FOURCC('x','v','i','d'), args.dst_video_fps,
-                                      img_to_show.size(), true);
-                    if (!video_writer.isOpened())
-                        throw std::runtime_error("can't create video writer");
+                    imwrite(output, img_to_show);
                 }
+                else                    //write video
+                {
+                    if (!video_writer.isOpened())
+                    {
+                        video_writer.open(output, CV_FOURCC('x','v','i','d'), 24,
+                                          img_to_show.size(), true);
+                        if (!video_writer.isOpened())
+                            throw std::runtime_error("can't create video writer");
+                    }
 
-                if (make_gray) cvtColor(img_to_show, img, CV_GRAY2BGR);
-                else cvtColor(img_to_show, img, CV_BGRA2BGR);
+                    if (make_gray) cvtColor(img_to_show, img, CV_GRAY2BGR);
+                    else cvtColor(img_to_show, img, CV_BGRA2BGR);
 
-                video_writer << img;
+                    video_writer << img;
+                }
             }
 
             handleKey((char)waitKey(3));
@@ -379,7 +282,6 @@ void App::run()
     }
 }
 
-
 void App::handleKey(char key)
 {
     switch (key)
@@ -442,7 +344,10 @@ void App::handleKey(char key)
 }
 
 
-inline void App::hogWorkBegin() { hog_work_begin = getTickCount(); }
+inline void App::hogWorkBegin()
+{
+    hog_work_begin = getTickCount();
+}
 
 inline void App::hogWorkEnd()
 {
@@ -458,8 +363,10 @@ inline string App::hogWorkFps() const
     return ss.str();
 }
 
-
-inline void App::workBegin() { work_begin = getTickCount(); }
+inline void App::workBegin()
+{
+    work_begin = getTickCount();
+}
 
 inline void App::workEnd()
 {
@@ -475,8 +382,9 @@ inline string App::workFps() const
     return ss.str();
 }
 
-double App::checkRectSimilarity(Size sz, 
-                                std::vector<Rect>& ob1, 
+
+double App::checkRectSimilarity(Size sz,
+                                std::vector<Rect>& ob1,
                                 std::vector<Rect>& ob2)
 {
     double final_test_result = 0.0;
@@ -484,20 +392,26 @@ double App::checkRectSimilarity(Size sz,
     size_t sz2 = ob2.size();
 
     if(sz1 != sz2)
+    {
         return sz1 > sz2 ? (double)(sz1 - sz2) : (double)(sz2 - sz1);
+    }
     else
     {
+        if(sz1==0 && sz2==0)
+            return 0;
         cv::Mat cpu_result(sz, CV_8UC1);
         cpu_result.setTo(0);
 
+
         for(vector<Rect>::const_iterator r = ob1.begin(); r != ob1.end(); r++)
-        {      
+        {
             cv::Mat cpu_result_roi(cpu_result, *r);
             cpu_result_roi.setTo(1);
             cpu_result.copyTo(cpu_result);
         }
         int cpu_area = cv::countNonZero(cpu_result > 0);
 
+
         cv::Mat gpu_result(sz, CV_8UC1);
         gpu_result.setTo(0);
         for(vector<Rect>::const_iterator r2 = ob2.begin(); r2 != ob2.end(); r2++)
@@ -510,10 +424,11 @@ double App::checkRectSimilarity(Size sz,
         cv::Mat result_;
         multiply(cpu_result, gpu_result, result_);
         int result = cv::countNonZero(result_ > 0);
-
-        final_test_result = 1.0 - (double)result/(double)cpu_area;
+        if(cpu_area!=0 && result!=0)
+            final_test_result = 1.0 - (double)result/(double)cpu_area;
+        else if(cpu_area==0 && result!=0)
+            final_test_result = -1;
     }
     return final_test_result;
-
 }
 
diff --git a/samples/ocl/pyrlk_optical_flow.cpp b/samples/ocl/pyrlk_optical_flow.cpp
index cc8d886f79..cefa928670 100644
--- a/samples/ocl/pyrlk_optical_flow.cpp
+++ b/samples/ocl/pyrlk_optical_flow.cpp
@@ -11,19 +11,20 @@ using namespace cv;
 using namespace cv::ocl;
 
 typedef unsigned char uchar;
-#define LOOP_NUM 10 
+#define LOOP_NUM 10
 int64 work_begin = 0;
 int64 work_end = 0;
 
-static void workBegin() 
-{ 
+static void workBegin()
+{
     work_begin = getTickCount();
 }
 static void workEnd()
 {
     work_end += (getTickCount() - work_begin);
 }
-static double getTime(){
+static double getTime()
+{
     return work_end * 1000. / getTickFrequency();
 }
 
@@ -93,14 +94,15 @@ int main(int argc, const char* argv[])
     //set this to save kernel compile time from second time you run
     ocl::setBinpath("./");
     const char* keys =
-        "{ h            | help           | false | print help message }"
-        "{ l            | left           |       | specify left image }"
-        "{ r            | right          |       | specify right image }"
-        "{ c            | camera         | 0     | enable camera capturing }"
-        "{ s            | use_cpu        | false | use cpu or gpu to process the image }"
-        "{ v            | video          |       | use video as input }"
-        "{ points       | points         | 1000  | specify points count [GoodFeatureToTrack] }"
-        "{ min_dist     | min_dist       | 0     | specify minimal distance between points [GoodFeatureToTrack] }";
+        "{ h   | help     | false           | print help message }"
+        "{ l   | left     |                 | specify left image }"
+        "{ r   | right    |                 | specify right image }"
+        "{ c   | camera   | 0               | specify camera id }"
+        "{ s   | use_cpu  | false           | use cpu or gpu to process the image }"
+        "{ v   | video    |                 | use video as input }"
+        "{ o   | output   | pyrlk_output.jpg| specify output save path when input is images }"
+        "{ p   | points   | 1000            | specify points count [GoodFeatureToTrack] }"
+        "{ m   | min_dist | 0               | specify minimal distance between points [GoodFeatureToTrack] }";
 
     CommandLineParser cmd(argc, argv, keys);
 
@@ -113,13 +115,13 @@ int main(int argc, const char* argv[])
     }
 
     bool defaultPicturesFail = false;
-    string fname0 = cmd.get<string>("left");
-    string fname1 = cmd.get<string>("right");
-    string vdofile = cmd.get<string>("video");
-    int points = cmd.get<int>("points");
-    double minDist = cmd.get<double>("min_dist");
+    string fname0 = cmd.get<string>("l");
+    string fname1 = cmd.get<string>("r");
+    string vdofile = cmd.get<string>("v");
+    string outfile = cmd.get<string>("o");
+    int points = cmd.get<int>("p");
+    double minDist = cmd.get<double>("m");
     bool useCPU = cmd.get<bool>("s");
-    bool useCamera = cmd.get<bool>("c");
     int inputName = cmd.get<int>("c");
 
     oclMat d_nextPts, d_status;
@@ -132,22 +134,9 @@ int main(int argc, const char* argv[])
     vector<unsigned char> status(points);
     vector<float> err;
 
-    if (frame0.empty() || frame1.empty())
-    {
-        useCamera = true;
-        defaultPicturesFail = true;
-        CvCapture* capture = 0;
-        capture = cvCaptureFromCAM( inputName );
-        if (!capture)
-        {
-            cout << "Can't load input images" << endl;
-            return -1;
-        }
-    }
-
     cout << "Points count : " << points << endl << endl;
 
-    if (useCamera)
+    if (frame0.empty() || frame1.empty())
     {
         CvCapture* capture = 0;
         Mat frame, frameCopy;
@@ -241,10 +230,10 @@ _cleanup_:
     else
     {
 nocamera:
-        for(int i = 0; i <= LOOP_NUM;i ++) 
+        for(int i = 0; i <= LOOP_NUM; i ++)
         {
             cout << "loop" << i << endl;
-            if (i > 0) workBegin();     
+            if (i > 0) workBegin();
 
             if (useCPU)
             {
@@ -274,8 +263,8 @@ nocamera:
                 cout << getTime() / LOOP_NUM << " ms" << endl;
 
                 drawArrows(frame0, pts, nextPts, status, Scalar(255, 0, 0));
-
                 imshow("PyrLK [Sparse]", frame0);
+                imwrite(outfile, frame0);
             }
         }
     }
diff --git a/samples/ocl/squares.cpp b/samples/ocl/squares.cpp
index 6b184161f7..48964ffb2e 100644
--- a/samples/ocl/squares.cpp
+++ b/samples/ocl/squares.cpp
@@ -6,7 +6,6 @@
 #include "opencv2/imgproc/imgproc.hpp"
 #include "opencv2/highgui/highgui.hpp"
 #include "opencv2/ocl/ocl.hpp"
-
 #include <iostream>
 #include <math.h>
 #include <string.h>
@@ -14,23 +13,50 @@
 using namespace cv;
 using namespace std;
 
-static void help()
+#define ACCURACY_CHECK 1
+
+#if ACCURACY_CHECK
+// check if two vectors of vector of points are near or not
+// prior assumption is that they are in correct order
+static bool checkPoints(
+    vector< vector<Point> > set1,
+    vector< vector<Point> > set2,
+    int maxDiff = 5)
 {
-    cout <<
-        "\nA program using OCL module pyramid scaling, Canny, dilate functions, threshold, split; cpu contours, contour simpification and\n"
-        "memory storage (it's got it all folks) to find\n"
-        "squares in a list of images pic1-6.png\n"
-        "Returns sequence of squares detected on the image.\n"
-        "the sequence is stored in the specified memory storage\n"
-        "Call:\n"
-        "./squares\n"
-        "Using OpenCV version %s\n" << CV_VERSION << "\n" << endl;
-}
+    if(set1.size() != set2.size())
+    {
+        return false;
+    }
+
+    for(vector< vector<Point> >::iterator it1 = set1.begin(), it2 = set2.begin();
+            it1 < set1.end() && it2 < set2.end(); it1 ++, it2 ++)
+    {
+        vector<Point> pts1 = *it1;
+        vector<Point> pts2 = *it2;
 
 
+        if(pts1.size() != pts2.size())
+        {
+            return false;
+        }
+        for(size_t i = 0; i < pts1.size(); i ++)
+        {
+            Point pt1 = pts1[i], pt2 = pts2[i];
+            if(std::abs(pt1.x - pt2.x) > maxDiff ||
+                    std::abs(pt1.y - pt2.y) > maxDiff)
+            {
+                return false;
+            }
+        }
+    }
+    return true;
+}
+#endif
+
 int thresh = 50, N = 11;
 const char* wndname = "OpenCL Square Detection Demo";
 
+
 // helper function:
 // finds a cosine of angle between vectors
 // from pt0->pt1 and from pt0->pt2
@@ -43,9 +69,92 @@ static double angle( Point pt1, Point pt2, Point pt0 )
     return (dx1*dx2 + dy1*dy2)/sqrt((dx1*dx1 + dy1*dy1)*(dx2*dx2 + dy2*dy2) + 1e-10);
 }
 
+
 // returns sequence of squares detected on the image.
 // the sequence is stored in the specified memory storage
 static void findSquares( const Mat& image, vector<vector<Point> >& squares )
+{
+    squares.clear();
+    Mat pyr, timg, gray0(image.size(), CV_8U), gray;
+
+    // down-scale and upscale the image to filter out the noise
+    pyrDown(image, pyr, Size(image.cols/2, image.rows/2));
+    pyrUp(pyr, timg, image.size());
+    vector<vector<Point> > contours;
+
+    // find squares in every color plane of the image
+    for( int c = 0; c < 3; c++ )
+    {
+        int ch[] = {c, 0};
+        mixChannels(&timg, 1, &gray0, 1, ch, 1);
+
+        // try several threshold levels
+        for( int l = 0; l < N; l++ )
+        {
+            // hack: use Canny instead of zero threshold level.
+            // Canny helps to catch squares with gradient shading
+            if( l == 0 )
+            {
+                // apply Canny. Take the upper threshold from slider
+                // and set the lower to 0 (which forces edges merging)
+                Canny(gray0, gray, 0, thresh, 5);
+                // dilate canny output to remove potential
+                // holes between edge segments
+                dilate(gray, gray, Mat(), Point(-1,-1));
+            }
+            else
+            {
+                // apply threshold if l!=0:
+                //     tgray(x,y) = gray(x,y) < (l+1)*255/N ? 255 : 0
+                cv::threshold(gray0, gray, (l+1)*255/N, 255, THRESH_BINARY);
+            }
+
+            // find contours and store them all as a list
+            findContours(gray, contours, CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE);
+
+            vector<Point> approx;
+
+            // test each contour
+            for( size_t i = 0; i < contours.size(); i++ )
+            {
+                // approximate contour with accuracy proportional
+                // to the contour perimeter
+                approxPolyDP(Mat(contours[i]), approx, arcLength(Mat(contours[i]), true)*0.02, true);
+
+                // square contours should have 4 vertices after approximation
+                // relatively large area (to filter out noisy contours)
+                // and be convex.
+                // Note: absolute value of an area is used because
+                // area may be positive or negative - in accordance with the
+                // contour orientation
+                if( approx.size() == 4 &&
+                        fabs(contourArea(Mat(approx))) > 1000 &&
+                        isContourConvex(Mat(approx)) )
+                {
+                    double maxCosine = 0;
+
+                    for( int j = 2; j < 5; j++ )
+                    {
+                        // find the maximum cosine of the angle between joint edges
+                        double cosine = fabs(angle(approx[j%4], approx[j-2], approx[j-1]));
+                        maxCosine = MAX(maxCosine, cosine);
+                    }
+
+                    // if cosines of all angles are small
+                    // (all angles are ~90 degree) then write quandrange
+                    // vertices to resultant sequence
+                    if( maxCosine < 0.3 )
+                        squares.push_back(approx);
+                }
+            }
+        }
+    }
+}
+
+
+// returns sequence of squares detected on the image.
+// the sequence is stored in the specified memory storage
+static void findSquares_ocl( const Mat& image, vector<vector<Point> >& squares )
 {
     squares.clear();
 
@@ -91,7 +200,6 @@ static void findSquares( const Mat& image, vector<vector<Point> >& squares )
             findContours(gray, contours, CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE);
 
             vector<Point> approx;
-
             // test each contour
             for( size_t i = 0; i < contours.size(); i++ )
             {
@@ -106,11 +214,10 @@ static void findSquares( const Mat& image, vector<vector<Point> >& squares )
                 // area may be positive or negative - in accordance with the
                 // contour orientation
                 if( approx.size() == 4 &&
-                    fabs(contourArea(Mat(approx))) > 1000 &&
-                    isContourConvex(Mat(approx)) )
+                        fabs(contourArea(Mat(approx))) > 1000 &&
+                        isContourConvex(Mat(approx)) )
                 {
                     double maxCosine = 0;
-
                     for( int j = 2; j < 5; j++ )
                     {
                         // find the maximum cosine of the angle between joint edges
@@ -139,40 +246,93 @@ static void drawSquares( Mat& image, const vector<vector<Point> >& squares )
         int n = (int)squares[i].size();
         polylines(image, &p, &n, 1, true, Scalar(0,255,0), 3, CV_AA);
     }
+}
+
 
-    imshow(wndname, image);
+// draw both pure-C++ and ocl square results onto a single image
+static Mat drawSquaresBoth( const Mat& image,
+                            const vector<vector<Point> >& sqsCPP,
+                            const vector<vector<Point> >& sqsOCL
+)
+{
+    Mat imgToShow(Size(image.cols * 2, image.rows), image.type());
+    Mat lImg = imgToShow(Rect(Point(0, 0), image.size()));
+    Mat rImg = imgToShow(Rect(Point(image.cols, 0), image.size()));
+    image.copyTo(lImg);
+    image.copyTo(rImg);
+    drawSquares(lImg, sqsCPP);
+    drawSquares(rImg, sqsOCL);
+    float fontScale = 0.8f;
+    Scalar white = Scalar::all(255), black = Scalar::all(0);
+
+    putText(lImg, "C++", Point(10, 20), FONT_HERSHEY_COMPLEX_SMALL, fontScale, black, 2);
+    putText(rImg, "OCL", Point(10, 20), FONT_HERSHEY_COMPLEX_SMALL, fontScale, black, 2);
+    putText(lImg, "C++", Point(10, 20), FONT_HERSHEY_COMPLEX_SMALL, fontScale, white, 1);
+    putText(rImg, "OCL", Point(10, 20), FONT_HERSHEY_COMPLEX_SMALL, fontScale, white, 1);
+
+    return imgToShow;
 }
 
 
-int main(int /*argc*/, char** /*argv*/)
+int main(int argc, char** argv)
 {
+    const char* keys =
+        "{ i | input   |                    | specify input image }"
+        "{ o | output  | squares_output.jpg | specify output save path}";
+    CommandLineParser cmd(argc, argv, keys);
+    string inputName = cmd.get<string>("i");
+    string outfile = cmd.get<string>("o");
+    if(inputName.empty())
+    {
+        cout << "Avaible options:" << endl;
+        cmd.printParams();
+        return 0;
+    }
 
-    //ocl::setBinpath("F:/kernel_bin");
     vector<ocl::Info> info;
     CV_Assert(ocl::getDevice(info));
-
-    static const char* names[] = { "pic1.png", "pic2.png", "pic3.png",
-        "pic4.png", "pic5.png", "pic6.png", 0 };
-    help();
+    int iterations = 10;
     namedWindow( wndname, 1 );
-    vector<vector<Point> > squares;
+    vector<vector<Point> > squares_cpu, squares_ocl;
 
-    for( int i = 0; names[i] != 0; i++ )
+    Mat image = imread(inputName, 1);
+    if( image.empty() )
     {
-        Mat image = imread(names[i], 1);
-        if( image.empty() )
-        {
-            cout << "Couldn't load " << names[i] << endl;
-            continue;
-        }
+        cout << "Couldn't load " << inputName << endl;
+        return -1;
+    }
+    int j = iterations;
+    int64 t_ocl = 0, t_cpp = 0;
+    //warm-ups
+    cout << "warming up ..." << endl;
+    findSquares(image, squares_cpu);
+    findSquares_ocl(image, squares_ocl);
+
+
+#if ACCURACY_CHECK
+    cout << "Checking ocl accuracy ... " << endl;
+    cout << (checkPoints(squares_cpu, squares_ocl) ? "Pass" : "Failed") << endl;
+#endif
+    do
+    {
+        int64 t_start = cv::getTickCount();
+        findSquares(image, squares_cpu);
+        t_cpp += cv::getTickCount() - t_start;
 
-        findSquares(image, squares);
-        drawSquares(image, squares);
 
-        int c = waitKey();
-        if( (char)c == 27 )
-            break;
+        t_start  = cv::getTickCount();
+        findSquares_ocl(image, squares_ocl);
+        t_ocl += cv::getTickCount() - t_start;
+        cout << "run loop: " << j << endl;
     }
+    while(--j);
+    cout << "cpp average time: " << 1000.0f * (double)t_cpp / getTickFrequency() / iterations << "ms" << endl;
+    cout << "ocl average time: " << 1000.0f * (double)t_ocl / getTickFrequency() / iterations << "ms" << endl;
+
+    Mat result = drawSquaresBoth(image, squares_cpu, squares_ocl);
+    imshow(wndname, result);
+    imwrite(outfile, result);
+    cvWaitKey(0);
 
     return 0;
 }
diff --git a/samples/ocl/stereo_match.cpp b/samples/ocl/stereo_match.cpp
index 7ac2c9a6f3..565744baa6 100644
--- a/samples/ocl/stereo_match.cpp
+++ b/samples/ocl/stereo_match.cpp
@@ -10,56 +10,45 @@ using namespace cv;
 using namespace std;
 using namespace ocl;
 
-bool help_showed = false;
-
-struct Params
-{
-    Params();
-    static Params read(int argc, char** argv);
-
-    string left;
-    string right;
-
-    string method_str() const
-    {
-        switch (method)
-        {
-        case BM: return "BM";
-        case BP: return "BP";
-        case CSBP: return "CSBP";
-        }
-        return "";
-    }
-    enum {BM, BP, CSBP} method;
-    int ndisp; // Max disparity + 1
-    enum {GPU, CPU} type;
-};
-
 
 struct App
 {
-    App(const Params& p);
+    App(CommandLineParser& cmd);
     void run();
     void handleKey(char key);
     void printParams() const;
 
-    void workBegin() { work_begin = getTickCount(); }
+    void workBegin()
+    {
+        work_begin = getTickCount();
+    }
     void workEnd()
     {
         int64 d = getTickCount() - work_begin;
         double f = getTickFrequency();
         work_fps = f / d;
     }
-
+    string method_str() const
+    {
+        switch (method)
+        {
+        case BM:
+            return "BM";
+        case BP:
+            return "BP";
+        case CSBP:
+            return "CSBP";
+        }
+        return "";
+    }
     string text() const
     {
         stringstream ss;
-        ss << "(" << p.method_str() << ") FPS: " << setiosflags(ios::left)
-            << setprecision(4) << work_fps;
+        ss << "(" << method_str() << ") FPS: " << setiosflags(ios::left)
+           << setprecision(4) << work_fps;
         return ss.str();
     }
 private:
-    Params p;
     bool running;
 
     Mat left_src, right_src;
@@ -72,42 +61,45 @@ private:
 
     int64 work_begin;
     double work_fps;
-};
 
-static void printHelp()
-{
-    cout << "Usage: stereo_match_gpu\n"
-        << "\t--left <left_view> --right <right_view> # must be rectified\n"
-        << "\t--method <stereo_match_method> # BM | BP | CSBP\n"
-        << "\t--ndisp <number> # number of disparity levels\n"
-        << "\t--type <device_type> # cpu | CPU | gpu | GPU\n";
-    help_showed = true;
-}
+    string l_img, r_img;
+    string out_img;
+    enum {BM, BP, CSBP} method;
+    int ndisp; // Max disparity + 1
+    enum {GPU, CPU} type;
+};
 
 int main(int argc, char** argv)
 {
+    const char* keys =
+        "{ h | help     | false                     | print help message }"
+        "{ l | left     |                           | specify left image }"
+        "{ r | right    |                           | specify right image }"
+        "{ m | method   | BM                        | specify match method(BM/BP/CSBP) }"
+        "{ n | ndisp    | 64                        |  specify number of disparity levels }"
+        "{ s | cpu_ocl  | false                     | use cpu or gpu as ocl device to process the image }"
+        "{ o | output   | stereo_match_output.jpg   | specify output path when input is images}";
+    CommandLineParser cmd(argc, argv, keys);
+    if (cmd.get<bool>("help"))
+    {
+        cout << "Avaible options:" << endl;
+        cmd.printParams();
+        return 0;
+    }
     try
     {
-        if (argc < 2)
-        {
-            printHelp();
-            return 1;
-        }
-
-        Params args = Params::read(argc, argv);
-        if (help_showed)
-            return -1;
+        App app(cmd);
+        int flag = CVCL_DEVICE_TYPE_GPU;
+        if(cmd.get<bool>("s") == true)
+            flag = CVCL_DEVICE_TYPE_CPU;
 
-        int flags[2] = { CVCL_DEVICE_TYPE_GPU, CVCL_DEVICE_TYPE_CPU };
         vector<Info> info;
-
-        if(getDevice(info, flags[args.type]) == 0)
+        if(getDevice(info, flag) == 0)
         {
             throw runtime_error("Error: Did not find a valid OpenCL device!");
         }
         cout << "Device name:" << info[0].DeviceName[0] << endl;
 
-        App app(args);
         app.run();
     }
     catch (const exception& e)
@@ -117,77 +109,39 @@ int main(int argc, char** argv)
     return 0;
 }
 
-
-Params::Params()
-{
-    method = BM;
-    ndisp = 64;
-    type = GPU;
-}
-
-
-Params Params::read(int argc, char** argv)
-{
-    Params p;
-
-    for (int i = 1; i < argc; i++)
-    {
-        if (string(argv[i]) == "--left") p.left = argv[++i];
-        else if (string(argv[i]) == "--right") p.right = argv[++i];
-        else if (string(argv[i]) == "--method")
-        {
-            if (string(argv[i + 1]) == "BM") p.method = BM;
-            else if (string(argv[i + 1]) == "BP") p.method = BP;
-            else if (string(argv[i + 1]) == "CSBP") p.method = CSBP;
-            else throw runtime_error("unknown stereo match method: " + string(argv[i + 1]));
-            i++;
-        }
-        else if (string(argv[i]) == "--ndisp") p.ndisp = atoi(argv[++i]);
-        else if (string(argv[i]) == "--type")
-        {
-            string t(argv[++i]);
-            if (t == "cpu" || t == "CPU")
-            {
-                p.type = CPU;
-            } 
-            else if (t == "gpu" || t == "GPU")
-            {
-                p.type = GPU;
-            }
-            else throw runtime_error("unknown device type: " + t);
-        }
-        else if (string(argv[i]) == "--help") printHelp();
-        else throw runtime_error("unknown key: " + string(argv[i]));
-    }
-
-    return p;
-}
-
-
-App::App(const Params& params)
-    : p(params), running(false)
+App::App(CommandLineParser& cmd)
+    : running(false),method(BM)
 {
     cout << "stereo_match_ocl sample\n";
     cout << "\nControls:\n"
-        << "\tesc - exit\n"
-        << "\tp - print current parameters\n"
-        << "\tg - convert source images into gray\n"
-        << "\tm - change stereo match method\n"
-        << "\ts - change Sobel prefiltering flag (for BM only)\n"
-        << "\t1/q - increase/decrease maximum disparity\n"
-        << "\t2/w - increase/decrease window size (for BM only)\n"
-        << "\t3/e - increase/decrease iteration count (for BP and CSBP only)\n"
-        << "\t4/r - increase/decrease level count (for BP and CSBP only)\n";
+         << "\tesc - exit\n"
+         << "\tp - print current parameters\n"
+         << "\tg - convert source images into gray\n"
+         << "\tm - change stereo match method\n"
+         << "\ts - change Sobel prefiltering flag (for BM only)\n"
+         << "\t1/q - increase/decrease maximum disparity\n"
+         << "\t2/w - increase/decrease window size (for BM only)\n"
+         << "\t3/e - increase/decrease iteration count (for BP and CSBP only)\n"
+         << "\t4/r - increase/decrease level count (for BP and CSBP only)\n";
+    l_img = cmd.get<string>("l");
+    r_img = cmd.get<string>("r");
+    string mstr = cmd.get<string>("m");
+    if(mstr == "BM") method = BM;
+    else if(mstr == "BP") method = BP;
+    else if(mstr == "CSBP") method = CSBP;
+    else cout << "unknown method!\n";
+    ndisp = cmd.get<int>("n");
+    out_img = cmd.get<string>("o");
 }
 
 
 void App::run()
 {
     // Load images
-    left_src = imread(p.left);
-    right_src = imread(p.right);
-    if (left_src.empty()) throw runtime_error("can't open file \"" + p.left + "\"");
-    if (right_src.empty()) throw runtime_error("can't open file \"" + p.right + "\"");
+    left_src = imread(l_img);
+    right_src = imread(r_img);
+    if (left_src.empty()) throw runtime_error("can't open file \"" + l_img + "\"");
+    if (right_src.empty()) throw runtime_error("can't open file \"" + r_img + "\"");
 
     cvtColor(left_src, left, CV_BGR2GRAY);
     cvtColor(right_src, right, CV_BGR2GRAY);
@@ -199,14 +153,15 @@ void App::run()
     imshow("right", right);
 
     // Set common parameters
-    bm.ndisp = p.ndisp;
-    bp.ndisp = p.ndisp;
-    csbp.ndisp = p.ndisp;
+    bm.ndisp = ndisp;
+    bp.ndisp = ndisp;
+    csbp.ndisp = ndisp;
 
     cout << endl;
     printParams();
 
     running = true;
+    bool written = false;
     while (running)
     {
 
@@ -214,9 +169,9 @@ void App::run()
         Mat disp;
         oclMat d_disp;
         workBegin();
-        switch (p.method)
+        switch (method)
         {
-        case Params::BM:
+        case BM:
             if (d_left.channels() > 1 || d_right.channels() > 1)
             {
                 cout << "BM doesn't support color images\n";
@@ -230,25 +185,28 @@ void App::run()
             }
             bm(d_left, d_right, d_disp);
             break;
-        case Params::BP:
+        case BP:
             bp(d_left, d_right, d_disp);
             break;
-        case Params::CSBP:
+        case CSBP:
             csbp(d_left, d_right, d_disp);
             break;
         }
-        ocl::finish();
         workEnd();
 
         // Show results
         d_disp.download(disp);
-        if (p.method != Params::BM)
+        if (method != BM)
         {
             disp.convertTo(disp, 0);
         }
         putText(disp, text(), Point(5, 25), FONT_HERSHEY_SIMPLEX, 1.0, Scalar::all(255));
         imshow("disparity", disp);
-
+        if(!written)
+        {
+            imwrite(out_img, disp);
+            written = true;
+        }
         handleKey((char)waitKey(3));
     }
 }
@@ -259,19 +217,19 @@ void App::printParams() const
     cout << "--- Parameters ---\n";
     cout << "image_size: (" << left.cols << ", " << left.rows << ")\n";
     cout << "image_channels: " << left.channels() << endl;
-    cout << "method: " << p.method_str() << endl
-        << "ndisp: " << p.ndisp << endl;
-    switch (p.method)
+    cout << "method: " << method_str() << endl
+         << "ndisp: " << ndisp << endl;
+    switch (method)
     {
-    case Params::BM:
+    case BM:
         cout << "win_size: " << bm.winSize << endl;
         cout << "prefilter_sobel: " << bm.preset << endl;
         break;
-    case Params::BP:
+    case BP:
         cout << "iter_count: " << bp.iters << endl;
         cout << "level_count: " << bp.levels << endl;
         break;
-    case Params::CSBP:
+    case CSBP:
         cout << "iter_count: " << csbp.iters << endl;
         cout << "level_count: " << csbp.levels << endl;
         break;
@@ -287,11 +245,13 @@ void App::handleKey(char key)
     case 27:
         running = false;
         break;
-    case 'p': case 'P':
+    case 'p':
+    case 'P':
         printParams();
         break;
-    case 'g': case 'G':
-        if (left.channels() == 1 && p.method != Params::BM)
+    case 'g':
+    case 'G':
+        if (left.channels() == 1 && method != BM)
         {
             left = left_src;
             right = right_src;
@@ -307,23 +267,25 @@ void App::handleKey(char key)
         imshow("left", left);
         imshow("right", right);
         break;
-    case 'm': case 'M':
-        switch (p.method)
+    case 'm':
+    case 'M':
+        switch (method)
         {
-        case Params::BM:
-            p.method = Params::BP;
+        case BM:
+            method = BP;
             break;
-        case Params::BP:
-            p.method = Params::CSBP;
+        case BP:
+            method = CSBP;
             break;
-        case Params::CSBP:
-            p.method = Params::BM;
+        case CSBP:
+            method = BM;
             break;
         }
-        cout << "method: " << p.method_str() << endl;
+        cout << "method: " << method_str() << endl;
         break;
-    case 's': case 'S':
-        if (p.method == Params::BM)
+    case 's':
+    case 'S':
+        if (method == BM)
         {
             switch (bm.preset)
             {
@@ -338,76 +300,80 @@ void App::handleKey(char key)
         }
         break;
     case '1':
-        p.ndisp = p.ndisp == 1 ? 8 : p.ndisp + 8;
-        cout << "ndisp: " << p.ndisp << endl;
-        bm.ndisp = p.ndisp;
-        bp.ndisp = p.ndisp;
-        csbp.ndisp = p.ndisp;
+        ndisp == 1 ? ndisp = 8 : ndisp += 8;
+        cout << "ndisp: " << ndisp << endl;
+        bm.ndisp = ndisp;
+        bp.ndisp = ndisp;
+        csbp.ndisp = ndisp;
         break;
-    case 'q': case 'Q':
-        p.ndisp = max(p.ndisp - 8, 1);
-        cout << "ndisp: " << p.ndisp << endl;
-        bm.ndisp = p.ndisp;
-        bp.ndisp = p.ndisp;
-        csbp.ndisp = p.ndisp;
+    case 'q':
+    case 'Q':
+        ndisp = max(ndisp - 8, 1);
+        cout << "ndisp: " << ndisp << endl;
+        bm.ndisp = ndisp;
+        bp.ndisp = ndisp;
+        csbp.ndisp = ndisp;
         break;
     case '2':
-        if (p.method == Params::BM)
+        if (method == BM)
         {
             bm.winSize = min(bm.winSize + 1, 51);
             cout << "win_size: " << bm.winSize << endl;
         }
         break;
-    case 'w': case 'W':
-        if (p.method == Params::BM)
+    case 'w':
+    case 'W':
+        if (method == BM)
         {
             bm.winSize = max(bm.winSize - 1, 2);
             cout << "win_size: " << bm.winSize << endl;
         }
         break;
     case '3':
-        if (p.method == Params::BP)
+        if (method == BP)
         {
             bp.iters += 1;
             cout << "iter_count: " << bp.iters << endl;
         }
-        else if (p.method == Params::CSBP)
+        else if (method == CSBP)
         {
             csbp.iters += 1;
             cout << "iter_count: " << csbp.iters << endl;
         }
         break;
-    case 'e': case 'E':
-        if (p.method == Params::BP)
+    case 'e':
+    case 'E':
+        if (method == BP)
         {
             bp.iters = max(bp.iters - 1, 1);
             cout << "iter_count: " << bp.iters << endl;
         }
-        else if (p.method == Params::CSBP)
+        else if (method == CSBP)
         {
             csbp.iters = max(csbp.iters - 1, 1);
             cout << "iter_count: " << csbp.iters << endl;
         }
         break;
     case '4':
-        if (p.method == Params::BP)
+        if (method == BP)
         {
             bp.levels += 1;
             cout << "level_count: " << bp.levels << endl;
         }
-        else if (p.method == Params::CSBP)
+        else if (method == CSBP)
         {
             csbp.levels += 1;
             cout << "level_count: " << csbp.levels << endl;
         }
         break;
-    case 'r': case 'R':
-        if (p.method == Params::BP)
+    case 'r':
+    case 'R':
+        if (method == BP)
         {
             bp.levels = max(bp.levels - 1, 1);
             cout << "level_count: " << bp.levels << endl;
         }
-        else if (p.method == Params::CSBP)
+        else if (method == CSBP)
         {
             csbp.levels = max(csbp.levels - 1, 1);
             cout << "level_count: " << csbp.levels << endl;
diff --git a/samples/ocl/surf_matcher.cpp b/samples/ocl/surf_matcher.cpp
index 038a8dc5cd..bee517fbca 100644
--- a/samples/ocl/surf_matcher.cpp
+++ b/samples/ocl/surf_matcher.cpp
@@ -1,48 +1,3 @@
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-//  By downloading, copying, installing or using the software you agree to this license.
-//  If you do not agree to this license, do not download, install,
-//  copy or use the software.
-//
-//
-//                           License Agreement
-//                For Open Source Computer Vision Library
-//
-// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
-// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// @Authors
-//    Peng Xiao, pengxiao@multicorewareinc.com
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-//   * Redistribution's of source code must retain the above copyright notice,
-//     this list of conditions and the following disclaimer.
-//
-//   * Redistribution's in binary form must reproduce the above copyright notice,
-//     this list of conditions and the following disclaimer in the documentation
-//     and/or other oclMaterials provided with the distribution.
-//
-//   * The name of the copyright holders may not be used to endorse or promote products
-//     derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors as is and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
 #include <iostream>
 #include <stdio.h>
 #include "opencv2/core/core.hpp"
@@ -61,27 +16,20 @@ const float GOOD_PORTION = 0.15f;
 
 namespace
 {
-void help();
-
-void help()
-{
-    std::cout << "\nThis program demonstrates using SURF_OCL features detector and descriptor extractor" << std::endl;
-    std::cout << "\nUsage:\n\tsurf_matcher --left <image1> --right <image2> [-c]" << std::endl;
-    std::cout << "\nExample:\n\tsurf_matcher --left box.png --right box_in_scene.png" << std::endl;
-}
 
 int64 work_begin = 0;
 int64 work_end = 0;
 
-void workBegin() 
-{ 
+void workBegin()
+{
     work_begin = getTickCount();
 }
 void workEnd()
 {
     work_end = getTickCount() - work_begin;
 }
-double getTime(){
+double getTime()
+{
     return work_end /((double)cvGetTickFrequency() * 1000.);
 }
 
@@ -114,17 +62,17 @@ struct SURFMatcher
 Mat drawGoodMatches(
     const Mat& cpu_img1,
     const Mat& cpu_img2,
-    const vector<KeyPoint>& keypoints1, 
-    const vector<KeyPoint>& keypoints2, 
+    const vector<KeyPoint>& keypoints1,
+    const vector<KeyPoint>& keypoints2,
     vector<DMatch>& matches,
     vector<Point2f>& scene_corners_
-    )
+)
 {
-    //-- Sort matches and preserve top 10% matches 
+    //-- Sort matches and preserve top 10% matches
     std::sort(matches.begin(), matches.end());
     std::vector< DMatch > good_matches;
     double minDist = matches.front().distance,
-        maxDist = matches.back().distance;
+           maxDist = matches.back().distance;
 
     const int ptsPairs = std::min(GOOD_PTS_MAX, (int)(matches.size() * GOOD_PORTION));
     for( int i = 0; i < ptsPairs; i++ )
@@ -139,8 +87,8 @@ Mat drawGoodMatches(
     // drawing the results
     Mat img_matches;
     drawMatches( cpu_img1, keypoints1, cpu_img2, keypoints2,
-        good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
-        vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS  );
+                 good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
+                 vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS  );
 
     //-- Localize the object
     std::vector<Point2f> obj;
@@ -154,28 +102,30 @@ Mat drawGoodMatches(
     }
     //-- Get the corners from the image_1 ( the object to be "detected" )
     std::vector<Point2f> obj_corners(4);
-    obj_corners[0] = cvPoint(0,0); obj_corners[1] = cvPoint( cpu_img1.cols, 0 );
-    obj_corners[2] = cvPoint( cpu_img1.cols, cpu_img1.rows ); obj_corners[3] = cvPoint( 0, cpu_img1.rows );
+    obj_corners[0] = cvPoint(0,0);
+    obj_corners[1] = cvPoint( cpu_img1.cols, 0 );
+    obj_corners[2] = cvPoint( cpu_img1.cols, cpu_img1.rows );
+    obj_corners[3] = cvPoint( 0, cpu_img1.rows );
     std::vector<Point2f> scene_corners(4);
-    
+
     Mat H = findHomography( obj, scene, CV_RANSAC );
     perspectiveTransform( obj_corners, scene_corners, H);
 
     scene_corners_ = scene_corners;
-    
+
     //-- Draw lines between the corners (the mapped object in the scene - image_2 )
-    line( img_matches, 
-        scene_corners[0] + Point2f( (float)cpu_img1.cols, 0), scene_corners[1] + Point2f( (float)cpu_img1.cols, 0), 
-        Scalar( 0, 255, 0), 2, CV_AA );
-    line( img_matches, 
-        scene_corners[1] + Point2f( (float)cpu_img1.cols, 0), scene_corners[2] + Point2f( (float)cpu_img1.cols, 0), 
-        Scalar( 0, 255, 0), 2, CV_AA );
-    line( img_matches, 
-        scene_corners[2] + Point2f( (float)cpu_img1.cols, 0), scene_corners[3] + Point2f( (float)cpu_img1.cols, 0), 
-        Scalar( 0, 255, 0), 2, CV_AA );
-    line( img_matches, 
-        scene_corners[3] + Point2f( (float)cpu_img1.cols, 0), scene_corners[0] + Point2f( (float)cpu_img1.cols, 0), 
-        Scalar( 0, 255, 0), 2, CV_AA );
+    line( img_matches,
+          scene_corners[0] + Point2f( (float)cpu_img1.cols, 0), scene_corners[1] + Point2f( (float)cpu_img1.cols, 0),
+          Scalar( 0, 255, 0), 2, CV_AA );
+    line( img_matches,
+          scene_corners[1] + Point2f( (float)cpu_img1.cols, 0), scene_corners[2] + Point2f( (float)cpu_img1.cols, 0),
+          Scalar( 0, 255, 0), 2, CV_AA );
+    line( img_matches,
+          scene_corners[2] + Point2f( (float)cpu_img1.cols, 0), scene_corners[3] + Point2f( (float)cpu_img1.cols, 0),
+          Scalar( 0, 255, 0), 2, CV_AA );
+    line( img_matches,
+          scene_corners[3] + Point2f( (float)cpu_img1.cols, 0), scene_corners[0] + Point2f( (float)cpu_img1.cols, 0),
+          Scalar( 0, 255, 0), 2, CV_AA );
     return img_matches;
 }
 
@@ -185,6 +135,21 @@ Mat drawGoodMatches(
 // use cpu findHomography interface to calculate the transformation matrix
 int main(int argc, char* argv[])
 {
+    const char* keys =
+        "{ h | help     | false           | print help message  }"
+        "{ l | left     |                 | specify left image  }"
+        "{ r | right    |                 | specify right image }"
+        "{ o | output   | SURF_output.jpg | specify output save path (only works in CPU or GPU only mode) }"
+        "{ c | use_cpu  | false           | use CPU algorithms  }"
+        "{ a | use_all  | false           | use both CPU and GPU algorithms}";
+    CommandLineParser cmd(argc, argv, keys);
+    if (cmd.get<bool>("help"))
+    {
+        std::cout << "Avaible options:" << std::endl;
+        cmd.printParams();
+        return 0;
+    }
+
     vector<cv::ocl::Info> info;
     if(cv::ocl::getDevice(info) == 0)
     {
@@ -195,54 +160,38 @@ int main(int argc, char* argv[])
 
     Mat cpu_img1, cpu_img2, cpu_img1_grey, cpu_img2_grey;
     oclMat img1, img2;
-    bool useCPU = false;
+    bool useCPU = cmd.get<bool>("c");
     bool useGPU = false;
-    bool useALL = false;
+    bool useALL = cmd.get<bool>("a");
+
+    string outpath = cmd.get<std::string>("o");
 
-    for (int i = 1; i < argc; ++i)
+    cpu_img1 = imread(cmd.get<std::string>("l"));
+    CV_Assert(!cpu_img1.empty());
+    cvtColor(cpu_img1, cpu_img1_grey, CV_BGR2GRAY);
+    img1 = cpu_img1_grey;
+
+    cpu_img2 = imread(cmd.get<std::string>("r"));
+    CV_Assert(!cpu_img2.empty());
+    cvtColor(cpu_img2, cpu_img2_grey, CV_BGR2GRAY);
+    img2 = cpu_img2_grey;
+
+    if(useALL)
     {
-        if (string(argv[i]) == "--left")
-        {
-            cpu_img1 = imread(argv[++i]);
-            CV_Assert(!cpu_img1.empty());
-            cvtColor(cpu_img1, cpu_img1_grey, CV_BGR2GRAY);
-            img1 = cpu_img1_grey;
-        }
-        else if (string(argv[i]) == "--right")
-        {
-            cpu_img2 = imread(argv[++i]);
-            CV_Assert(!cpu_img2.empty());
-            cvtColor(cpu_img2, cpu_img2_grey, CV_BGR2GRAY);
-            img2 = cpu_img2_grey;
-        }
-        else if (string(argv[i]) == "-c")
-        {
-            useCPU = true;
-            useGPU = false;
-            useALL = false;
-        }else if(string(argv[i]) == "-g")
-        {
-            useGPU = true;
-            useCPU = false;
-            useALL = false;
-        }else if(string(argv[i]) == "-a")
-        {
-            useALL = true;
-            useCPU = false;
-            useGPU = false;
-        }
-        else if (string(argv[i]) == "--help")
-        {
-            help();
-            return -1;
-        }
+        useCPU = false;
+        useGPU = false;
     }
+    else if(useCPU==false && useALL==false)
+    {
+        useGPU = true;
+    }
+
     if(!useCPU)
     {
         std::cout
-            << "Device name:"
-            << info[0].DeviceName[0]
-        << std::endl;
+                << "Device name:"
+                << info[0].DeviceName[0]
+                << std::endl;
     }
     double surf_time = 0.;
 
@@ -262,12 +211,12 @@ int main(int argc, char* argv[])
     //instantiate detectors/matchers
     SURFDetector<SURF>     cpp_surf;
     SURFDetector<SURF_OCL> ocl_surf;
-    
+
     SURFMatcher<BFMatcher>      cpp_matcher;
     SURFMatcher<BFMatcher_OCL>  ocl_matcher;
 
     //-- start of timing section
-    if (useCPU) 
+    if (useCPU)
     {
         for (int i = 0; i <= LOOP_NUM; i++)
         {
@@ -298,7 +247,8 @@ int main(int argc, char* argv[])
 
         surf_time = getTime();
         std::cout << "SURF run time: " << surf_time / LOOP_NUM << " ms" << std::endl<<"\n";
-    }else
+    }
+    else
     {
         //cpu runs
         for (int i = 0; i <= LOOP_NUM; i++)
@@ -353,14 +303,14 @@ int main(int argc, char* argv[])
             for(size_t i = 0; i < cpu_corner.size(); i++)
             {
                 if((std::abs(cpu_corner[i].x - gpu_corner[i].x) > 10)
-                    ||(std::abs(cpu_corner[i].y - gpu_corner[i].y) > 10))
+                        ||(std::abs(cpu_corner[i].y - gpu_corner[i].y) > 10))
                 {
                     std::cout<<"Failed\n";
                     result = false;
                     break;
                 }
                 result = true;
-            } 
+            }
             if(result)
                 std::cout<<"Passed\n";
         }
@@ -371,12 +321,15 @@ int main(int argc, char* argv[])
     {
         namedWindow("cpu surf matches", 0);
         imshow("cpu surf matches", img_matches);
+        imwrite(outpath, img_matches);
     }
     else if(useGPU)
     {
         namedWindow("ocl surf matches", 0);
         imshow("ocl surf matches", img_matches);
-    }else
+        imwrite(outpath, img_matches);
+    }
+    else
     {
         namedWindow("cpu surf matches", 0);
         imshow("cpu surf matches", img_matches);
diff --git a/samples/ocl/tvl1_optical_flow.cpp b/samples/ocl/tvl1_optical_flow.cpp
new file mode 100644
index 0000000000..cff9692ed6
--- /dev/null
+++ b/samples/ocl/tvl1_optical_flow.cpp
@@ -0,0 +1,265 @@
+#include <iostream>
+#include <vector>
+#include <iomanip>
+
+#include "opencv2/highgui/highgui.hpp"
+#include "opencv2/ocl/ocl.hpp"
+#include "opencv2/video/video.hpp"
+
+using namespace std;
+using namespace cv;
+using namespace cv::ocl;
+
+typedef unsigned char uchar;
+#define LOOP_NUM 10
+int64 work_begin = 0;
+int64 work_end = 0;
+
+static void workBegin()
+{
+    work_begin = getTickCount();
+}
+static void workEnd()
+{
+    work_end += (getTickCount() - work_begin);
+}
+static double getTime()
+{
+    return work_end * 1000. / getTickFrequency();
+}
+
+template <typename T> inline T clamp (T x, T a, T b)
+{
+    return ((x) > (a) ? ((x) < (b) ? (x) : (b)) : (a));
+}
+
+template <typename T> inline T mapValue(T x, T a, T b, T c, T d)
+{
+    x = clamp(x, a, b);
+    return c + (d - c) * (x - a) / (b - a);
+}
+
+static void getFlowField(const Mat& u, const Mat& v, Mat& flowField)
+{
+    float maxDisplacement = 1.0f;
+
+    for (int i = 0; i < u.rows; ++i)
+    {
+        const float* ptr_u = u.ptr<float>(i);
+        const float* ptr_v = v.ptr<float>(i);
+
+        for (int j = 0; j < u.cols; ++j)
+        {
+            float d = max(fabsf(ptr_u[j]), fabsf(ptr_v[j]));
+
+            if (d > maxDisplacement)
+                maxDisplacement = d;
+        }
+    }
+
+    flowField.create(u.size(), CV_8UC4);
+
+    for (int i = 0; i < flowField.rows; ++i)
+    {
+        const float* ptr_u = u.ptr<float>(i);
+        const float* ptr_v = v.ptr<float>(i);
+
+
+        Vec4b* row = flowField.ptr<Vec4b>(i);
+
+        for (int j = 0; j < flowField.cols; ++j)
+        {
+            row[j][0] = 0;
+            row[j][1] = static_cast<unsigned char> (mapValue (-ptr_v[j], -maxDisplacement, maxDisplacement, 0.0f, 255.0f));
+            row[j][2] = static_cast<unsigned char> (mapValue ( ptr_u[j], -maxDisplacement, maxDisplacement, 0.0f, 255.0f));
+            row[j][3] = 255;
+        }
+    }
+}
+
+
+int main(int argc, const char* argv[])
+{
+    static std::vector<Info> ocl_info;
+    ocl::getDevice(ocl_info);
+    //if you want to use undefault device, set it here
+    setDevice(ocl_info[0]);
+
+    //set this to save kernel compile time from second time you run
+    ocl::setBinpath("./");
+    const char* keys =
+        "{ h   | help       | false           | print help message }"
+        "{ l   | left       |                 | specify left image }"
+        "{ r   | right      |                 | specify right image }"
+        "{ o   | output     | tvl1_output.jpg | specify output save path }"
+        "{ c   | camera     | 0               | enable camera capturing }"
+        "{ s   | use_cpu    | false           | use cpu or gpu to process the image }"
+        "{ v   | video      |                 | use video as input }";
+
+    CommandLineParser cmd(argc, argv, keys);
+
+    if (cmd.get<bool>("help"))
+    {
+        cout << "Usage: pyrlk_optical_flow [options]" << endl;
+        cout << "Avaible options:" << endl;
+        cmd.printParams();
+        return 0;
+    }
+
+    bool defaultPicturesFail = false;
+    string fname0 = cmd.get<string>("l");
+    string fname1 = cmd.get<string>("r");
+    string vdofile = cmd.get<string>("v");
+    string outpath = cmd.get<string>("o");
+    bool useCPU = cmd.get<bool>("s");
+    bool useCamera = cmd.get<bool>("c");
+    int inputName = cmd.get<int>("c");
+
+    Mat frame0 = imread(fname0, cv::IMREAD_GRAYSCALE);
+    Mat frame1 = imread(fname1, cv::IMREAD_GRAYSCALE);
+    cv::Ptr<cv::DenseOpticalFlow> alg = cv::createOptFlow_DualTVL1();
+    cv::ocl::OpticalFlowDual_TVL1_OCL d_alg;
+
+
+    Mat flow, show_flow;
+    Mat flow_vec[2];
+    if (frame0.empty() || frame1.empty())
+    {
+        useCamera = true;
+        defaultPicturesFail = true;
+        CvCapture* capture = 0;
+        capture = cvCaptureFromCAM( inputName );
+        if (!capture)
+        {
+            cout << "Can't load input images" << endl;
+            return -1;
+        }
+    }
+
+
+    if (useCamera)
+    {
+        CvCapture* capture = 0;
+        Mat frame, frameCopy;
+        Mat frame0Gray, frame1Gray;
+        Mat ptr0, ptr1;
+
+        if(vdofile == "")
+            capture = cvCaptureFromCAM( inputName );
+        else
+            capture = cvCreateFileCapture(vdofile.c_str());
+
+        int c = inputName ;
+        if(!capture)
+        {
+            if(vdofile == "")
+                cout << "Capture from CAM " << c << " didn't work" << endl;
+            else
+                cout << "Capture from file " << vdofile << " failed" <<endl;
+            if (defaultPicturesFail)
+            {
+                return -1;
+            }
+            goto nocamera;
+        }
+
+        cout << "In capture ..." << endl;
+        for(int i = 0;; i++)
+        {
+            frame = cvQueryFrame( capture );
+            if( frame.empty() )
+                break;
+
+            if (i == 0)
+            {
+                frame.copyTo( frame0 );
+                cvtColor(frame0, frame0Gray, COLOR_BGR2GRAY);
+            }
+            else
+            {
+                if (i%2 == 1)
+                {
+                    frame.copyTo(frame1);
+                    cvtColor(frame1, frame1Gray, COLOR_BGR2GRAY);
+                    ptr0 = frame0Gray;
+                    ptr1 = frame1Gray;
+                }
+                else
+                {
+                    frame.copyTo(frame0);
+                    cvtColor(frame0, frame0Gray, COLOR_BGR2GRAY);
+                    ptr0 = frame1Gray;
+                    ptr1 = frame0Gray;
+                }
+
+                if (useCPU)
+                {
+                    alg->calc(ptr0, ptr1, flow);
+                    split(flow, flow_vec);
+                }
+                else
+                {
+                    oclMat d_flowx, d_flowy;
+                    d_alg(oclMat(ptr0), oclMat(ptr1), d_flowx, d_flowy);
+                    d_flowx.download(flow_vec[0]);
+                    d_flowy.download(flow_vec[1]);
+                }
+                if (i%2 == 1)
+                    frame1.copyTo(frameCopy);
+                else
+                    frame0.copyTo(frameCopy);
+                getFlowField(flow_vec[0], flow_vec[1], show_flow);
+                imshow("PyrLK [Sparse]", show_flow);
+            }
+
+            if( waitKey( 10 ) >= 0 )
+                goto _cleanup_;
+        }
+
+        waitKey(0);
+
+_cleanup_:
+        cvReleaseCapture( &capture );
+    }
+    else
+    {
+nocamera:
+        oclMat d_flowx, d_flowy;
+        for(int i = 0; i <= LOOP_NUM; i ++)
+        {
+            cout << "loop" << i << endl;
+
+            if (i > 0) workBegin();
+            if (useCPU)
+            {
+                alg->calc(frame0, frame1, flow);
+                split(flow, flow_vec);
+            }
+            else
+            {
+                d_alg(oclMat(frame0), oclMat(frame1), d_flowx, d_flowy);
+                d_flowx.download(flow_vec[0]);
+                d_flowy.download(flow_vec[1]);
+            }
+            if (i > 0 && i <= LOOP_NUM)
+                workEnd();
+
+            if (i == LOOP_NUM)
+            {
+                if (useCPU)
+                    cout << "average CPU time (noCamera) : ";
+                else
+                    cout << "average GPU time (noCamera) : ";
+                cout << getTime() / LOOP_NUM << " ms" << endl;
+
+                getFlowField(flow_vec[0], flow_vec[1], show_flow);
+                imshow("PyrLK [Sparse]", show_flow);
+                imwrite(outpath, show_flow);
+            }
+        }
+    }
+
+    waitKey();
+
+    return 0;
+}
\ No newline at end of file

From d58421c08eb578fe449e6b90cbeb7731fdb1a44b Mon Sep 17 00:00:00 2001
From: Roman Donchenko <roman.donchenko@itseez.com>
Date: Wed, 19 Jun 2013 14:45:03 +0400
Subject: [PATCH 20/27] Make version-related test properties more useful.

Namely, normalize their names to a common convention and remove useless text
from their values.
---
 modules/ts/src/ts_func.cpp | 20 +++++++++++---------
 1 file changed, 11 insertions(+), 9 deletions(-)

diff --git a/modules/ts/src/ts_func.cpp b/modules/ts/src/ts_func.cpp
index e2998149d5..9b6b535816 100644
--- a/modules/ts/src/ts_func.cpp
+++ b/modules/ts/src/ts_func.cpp
@@ -2940,27 +2940,29 @@ MatComparator::operator()(const char* expr1, const char* expr2,
 
 void printVersionInfo(bool useStdOut)
 {
-    ::testing::Test::RecordProperty("CV_VERSION", CV_VERSION);
+    ::testing::Test::RecordProperty("cv_version", CV_VERSION);
     if(useStdOut) std::cout << "OpenCV version: " << CV_VERSION << std::endl;
 
     std::string buildInfo( cv::getBuildInformation() );
 
     size_t pos1 = buildInfo.find("Version control");
-    size_t pos2 = buildInfo.find("\n", pos1);\
+    size_t pos2 = buildInfo.find('\n', pos1);
     if(pos1 != std::string::npos && pos2 != std::string::npos)
     {
-        std::string ver( buildInfo.substr(pos1, pos2-pos1) );
-        ::testing::Test::RecordProperty("Version_control", ver);
-        if(useStdOut) std::cout << ver << std::endl;
+        size_t value_start = buildInfo.rfind(' ', pos2) + 1;
+        std::string ver( buildInfo.substr(value_start, pos2 - value_start) );
+        ::testing::Test::RecordProperty("cv_vcs_version", ver);
+        if (useStdOut) std::cout << "OpenCV VCS version: " << ver << std::endl;
     }
 
     pos1 = buildInfo.find("inner version");
-    pos2 = buildInfo.find("\n", pos1);\
+    pos2 = buildInfo.find('\n', pos1);
     if(pos1 != std::string::npos && pos2 != std::string::npos)
     {
-        std::string ver( buildInfo.substr(pos1, pos2-pos1) );
-        ::testing::Test::RecordProperty("inner_version", ver);
-        if(useStdOut) std::cout << ver << std::endl;
+        size_t value_start = buildInfo.rfind(' ', pos2) + 1;
+        std::string ver( buildInfo.substr(value_start, pos2 - value_start) );
+        ::testing::Test::RecordProperty("cv_inner_vcs_version", ver);
+        if(useStdOut) std::cout << "Inner VCS version: " << ver << std::endl;
     }
 
 #ifdef CV_PARALLEL_FRAMEWORK

From 1ed5fb937d34348becbf9fa3c837d1bdfe9c6f95 Mon Sep 17 00:00:00 2001
From: Roman Donchenko <roman.donchenko@itseez.com>
Date: Wed, 19 Jun 2013 15:39:11 +0400
Subject: [PATCH 21/27] Give cv::ocl::CLAHE a virtual destructor, for the usual
 reasons.

---
 modules/ocl/include/opencv2/ocl/ocl.hpp | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/modules/ocl/include/opencv2/ocl/ocl.hpp b/modules/ocl/include/opencv2/ocl/ocl.hpp
index d6dd4b983c..3324b7932e 100644
--- a/modules/ocl/include/opencv2/ocl/ocl.hpp
+++ b/modules/ocl/include/opencv2/ocl/ocl.hpp
@@ -520,6 +520,8 @@ namespace cv
             virtual Size getTilesGridSize() const = 0;
 
             virtual void collectGarbage() = 0;
+
+            virtual ~CLAHE() {}
         };
         CV_EXPORTS Ptr<cv::ocl::CLAHE> createCLAHE(double clipLimit = 40.0, Size tileGridSize = Size(8, 8));
         

From c1f4fe1637aa1279d7eef7ef95f26ea92c9de967 Mon Sep 17 00:00:00 2001
From: peng xiao <hisenxpress@gmail.com>
Date: Thu, 20 Jun 2013 11:26:22 +0800
Subject: [PATCH 22/27] Fix a bug of convertTo. The bug was found that all
 3-channel oclMat's were converted to 4-channel oclMat's after using convertTo
 function.

---
 modules/ocl/src/matrix_operations.cpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/ocl/src/matrix_operations.cpp b/modules/ocl/src/matrix_operations.cpp
index 268a1fe9b5..172dfa5a89 100644
--- a/modules/ocl/src/matrix_operations.cpp
+++ b/modules/ocl/src/matrix_operations.cpp
@@ -394,7 +394,7 @@ void cv::ocl::oclMat::convertTo( oclMat &dst, int rtype, double alpha, double be
     if( rtype < 0 )
         rtype = type();
     else
-        rtype = CV_MAKETYPE(CV_MAT_DEPTH(rtype), oclchannels());
+        rtype = CV_MAKETYPE(CV_MAT_DEPTH(rtype), channels());
 
     //int scn = channels();
     int sdepth = depth(), ddepth = CV_MAT_DEPTH(rtype);

From 3e2c4563134e2b88408ad7b1a280a312eb46d4a4 Mon Sep 17 00:00:00 2001
From: Roman Donchenko <roman.donchenko@itseez.com>
Date: Thu, 20 Jun 2013 14:27:51 +0400
Subject: [PATCH 23/27] A few minor improvements to the XLS report generator.

* In comparison column headers, switched the order of labels, so that
  it's "to" vs "from".

* When a test was present, but not run successfully, put its status in
  the corresponding cell instead of coloring it gray.
---
 modules/ts/misc/xls-report.py | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/modules/ts/misc/xls-report.py b/modules/ts/misc/xls-report.py
index f6278bae00..c13842cdca 100755
--- a/modules/ts/misc/xls-report.py
+++ b/modules/ts/misc/xls-report.py
@@ -4,6 +4,7 @@ from __future__ import division
 
 import ast
 import logging
+import numbers
 import os, os.path
 import re
 
@@ -52,8 +53,7 @@ def collect_xml(collection, configuration, xml_fullname):
 
     for test in sorted(parseLogFile(xml_fullname)):
         test_results = module_tests.setdefault((test.shortName(), test.param()), {})
-        if test.status == 'run':
-            test_results[configuration] = test.get("gmean")
+        test_results[configuration] = test.get("gmean") if test.status == 'run' else test.status
 
 def main():
     arg_parser = ArgumentParser(description='Build an XLS performance report.')
@@ -117,7 +117,7 @@ def main():
 
         for i, caption in enumerate(['Module', 'Test', 'Image\nsize', 'Data\ntype', 'Parameters']
                 + config_names + [None]
-                + [comp['from'] + '\nvs\n' + comp['to'] for comp in sheet_comparisons]):
+                + [comp['to'] + '\nvs\n' + comp['from'] for comp in sheet_comparisons]):
             sheet.row(0).write(i, caption, header_style)
 
         row = 1
@@ -143,13 +143,13 @@ def main():
                         sheet.write(row, 5 + i, None, no_time_style)
 
                 for i, comp in enumerate(sheet_comparisons):
-                    left = configs.get(comp["from"])
-                    right = configs.get(comp["to"])
+                    cmp_from = configs.get(comp["from"])
+                    cmp_to = configs.get(comp["to"])
                     col = 5 + len(config_names) + 1 + i
 
-                    if left is not None and right is not None:
+                    if isinstance(cmp_from, numbers.Number) and isinstance(cmp_to, numbers.Number):
                         try:
-                            speedup = left / right
+                            speedup = cmp_from / cmp_to
                             sheet.write(row, col, speedup, good_speedup_style if speedup > 1.1 else
                                                            bad_speedup_style  if speedup < 0.9 else
                                                            speedup_style)

From 57317c3196fb9d5fbe9e00b16453dea7d534ac11 Mon Sep 17 00:00:00 2001
From: Roman Donchenko <roman.donchenko@itseez.com>
Date: Thu, 20 Jun 2013 19:39:02 +0400
Subject: [PATCH 24/27] Use log formatting as intended.

---
 modules/ts/misc/xls-report.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/modules/ts/misc/xls-report.py b/modules/ts/misc/xls-report.py
index c13842cdca..e79bb123dd 100755
--- a/modules/ts/misc/xls-report.py
+++ b/modules/ts/misc/xls-report.py
@@ -79,7 +79,7 @@ def main():
                 sheet_conf = ast.literal_eval(sheet_conf_file.read())
         except Exception:
             sheet_conf = {}
-            logging.debug('no sheet.conf for {}'.format(sheet_path))
+            logging.debug('no sheet.conf for %s', sheet_path)
 
         sheet_conf = dict(global_conf.items() + sheet_conf.items())
 
@@ -90,14 +90,14 @@ def main():
                 config_names = [p for p in os.listdir(sheet_path)
                     if os.path.isdir(os.path.join(sheet_path, p))]
             except Exception as e:
-                logging.warning(e)
+                logging.warning('error while determining configuration names for %s: %s', sheet_path, e)
                 continue
 
         collection = {}
 
         for configuration, configuration_path in \
                 [(c, os.path.join(sheet_path, c))  for c in config_names]:
-            logging.info('processing {}'.format(configuration_path))
+            logging.info('processing %s', configuration_path)
             for xml_fullname in glob(os.path.join(configuration_path, '*.xml')):
                 collect_xml(collection, configuration, xml_fullname)
 

From e12963826337daa5ff67198e25b17f0dfdbf2edf Mon Sep 17 00:00:00 2001
From: peng xiao <hisenxpress@gmail.com>
Date: Fri, 21 Jun 2013 14:05:29 +0800
Subject: [PATCH 25/27] Add a workaround to interpolate between oclMat and
 Input/OutputArray.

---
 modules/core/include/opencv2/core/core.hpp |  3 ++-
 modules/core/src/matrix.cpp                | 30 ++++++++++++++++++++++
 modules/ocl/include/opencv2/ocl/ocl.hpp    |  8 ++++++
 modules/ocl/src/matrix_operations.cpp      | 29 +++++++++++++++++++++
 4 files changed, 69 insertions(+), 1 deletion(-)

diff --git a/modules/core/include/opencv2/core/core.hpp b/modules/core/include/opencv2/core/core.hpp
index 2b7791958f..5ff31fe3a8 100644
--- a/modules/core/include/opencv2/core/core.hpp
+++ b/modules/core/include/opencv2/core/core.hpp
@@ -1322,7 +1322,8 @@ public:
         EXPR              = 6 << KIND_SHIFT,
         OPENGL_BUFFER     = 7 << KIND_SHIFT,
         OPENGL_TEXTURE    = 8 << KIND_SHIFT,
-        GPU_MAT           = 9 << KIND_SHIFT
+        GPU_MAT           = 9 << KIND_SHIFT,
+        OCL_MAT           =10 << KIND_SHIFT
     };
     _InputArray();
 
diff --git a/modules/core/src/matrix.cpp b/modules/core/src/matrix.cpp
index 7acb0e0dbd..c4c0041dd9 100644
--- a/modules/core/src/matrix.cpp
+++ b/modules/core/src/matrix.cpp
@@ -980,6 +980,11 @@ Mat _InputArray::getMat(int i) const
         return !v.empty() ? Mat(size(i), t, (void*)&v[0]) : Mat();
     }
 
+    if( k == OCL_MAT )
+    {
+        CV_Error(-1, "Not implemented");
+    }
+
     CV_Assert( k == STD_VECTOR_MAT );
     //if( k == STD_VECTOR_MAT )
     {
@@ -1062,6 +1067,11 @@ void _InputArray::getMatVector(vector<Mat>& mv) const
         return;
     }
 
+    if( k == OCL_MAT )
+    {
+        CV_Error(-1, "Not implemented");
+    }
+
     CV_Assert( k == STD_VECTOR_MAT );
     //if( k == STD_VECTOR_MAT )
     {
@@ -1189,6 +1199,11 @@ Size _InputArray::size(int i) const
         return tex->size();
     }
 
+    if( k == OCL_MAT )
+    {
+        CV_Error(-1, "Not implemented");
+    }
+
     CV_Assert( k == GPU_MAT );
     //if( k == GPU_MAT )
     {
@@ -1303,6 +1318,11 @@ bool _InputArray::empty() const
     if( k == OPENGL_TEXTURE )
         return ((const ogl::Texture2D*)obj)->empty();
 
+    if( k == OCL_MAT )
+    {
+        CV_Error(-1, "Not implemented");
+    }
+
     CV_Assert( k == GPU_MAT );
     //if( k == GPU_MAT )
         return ((const gpu::GpuMat*)obj)->empty();
@@ -1523,6 +1543,11 @@ void _OutputArray::create(int dims, const int* sizes, int mtype, int i, bool all
         return;
     }
 
+    if( k == OCL_MAT )
+    {
+        CV_Error(-1, "Not implemented");
+    }
+
     if( k == NONE )
     {
         CV_Error(CV_StsNullPtr, "create() called for the missing output array" );
@@ -1634,6 +1659,11 @@ void _OutputArray::release() const
         return;
     }
 
+    if( k == OCL_MAT )
+    {
+        CV_Error(-1, "Not implemented");
+    }
+
     CV_Assert( k == STD_VECTOR_MAT );
     //if( k == STD_VECTOR_MAT )
     {
diff --git a/modules/ocl/include/opencv2/ocl/ocl.hpp b/modules/ocl/include/opencv2/ocl/ocl.hpp
index d6dd4b983c..9fdd8f3e99 100644
--- a/modules/ocl/include/opencv2/ocl/ocl.hpp
+++ b/modules/ocl/include/opencv2/ocl/ocl.hpp
@@ -248,6 +248,11 @@ namespace cv
             operator Mat() const;
             void download(cv::Mat &m) const;
 
+            //! convert to _InputArray
+            operator _InputArray();
+
+            //! convert to _OutputArray
+            operator _OutputArray();
 
             //! returns a new oclMatrix header for the specified row
             oclMat row(int y) const;
@@ -387,6 +392,9 @@ namespace cv
             int wholecols;
         };
 
+        // convert InputArray/OutputArray to oclMat
+        CV_EXPORTS oclMat& getOclMat(InputArray src);
+        CV_EXPORTS oclMat& getOclMat(OutputArray src);
 
         ///////////////////// mat split and merge /////////////////////////////////
         //! Compose a multi-channel array from several single-channel arrays
diff --git a/modules/ocl/src/matrix_operations.cpp b/modules/ocl/src/matrix_operations.cpp
index 268a1fe9b5..dc7deebe38 100644
--- a/modules/ocl/src/matrix_operations.cpp
+++ b/modules/ocl/src/matrix_operations.cpp
@@ -74,6 +74,7 @@ namespace cv
     }
 }
 
+
 ////////////////////////////////////////////////////////////////////////
 // convert_C3C4
 static void convert_C3C4(const cl_mem &src, oclMat &dst)
@@ -227,6 +228,34 @@ void cv::ocl::oclMat::upload(const Mat &m)
     //download_channels = m.channels();
 }
 
+cv::ocl::oclMat::operator cv::_InputArray()
+{
+    _InputArray newInputArray;
+    newInputArray.flags = cv::_InputArray::OCL_MAT;
+    newInputArray.obj   = reinterpret_cast<void *>(this);
+    return newInputArray;
+}
+
+cv::ocl::oclMat::operator cv::_OutputArray()
+{
+    _OutputArray newOutputArray;
+    newOutputArray.flags = cv::_InputArray::OCL_MAT;
+    newOutputArray.obj   = reinterpret_cast<void *>(this);
+    return newOutputArray;
+}
+
+cv::ocl::oclMat& cv::ocl::getOclMat(InputArray src)
+{
+    CV_Assert(src.flags & cv::_InputArray::OCL_MAT);
+    return *reinterpret_cast<oclMat*>(src.obj);
+}
+
+cv::ocl::oclMat& cv::ocl::getOclMat(OutputArray src)
+{
+    CV_Assert(src.flags & cv::_InputArray::OCL_MAT);
+    return *reinterpret_cast<oclMat*>(src.obj);
+}
+
 void cv::ocl::oclMat::download(cv::Mat &m) const
 {
     CV_DbgAssert(!this->empty());

From 6326739b443c0e87a251446893ee18225eeaf428 Mon Sep 17 00:00:00 2001
From: yao <bitwangyaoyao@gmail.com>
Date: Fri, 21 Jun 2013 14:50:08 +0800
Subject: [PATCH 26/27] a bug fix in stereo_match sample

---
 samples/ocl/stereo_match.cpp | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/samples/ocl/stereo_match.cpp b/samples/ocl/stereo_match.cpp
index 565744baa6..abe75c70e1 100644
--- a/samples/ocl/stereo_match.cpp
+++ b/samples/ocl/stereo_match.cpp
@@ -192,10 +192,9 @@ void App::run()
             csbp(d_left, d_right, d_disp);
             break;
         }
-        workEnd();
-
         // Show results
         d_disp.download(disp);
+        workEnd();
         if (method != BM)
         {
             disp.convertTo(disp, 0);

From 290c8db0a85ff6e4a9d84243624852a21190598f Mon Sep 17 00:00:00 2001
From: peng xiao <hisenxpress@gmail.com>
Date: Fri, 21 Jun 2013 14:51:23 +0800
Subject: [PATCH 27/27] Revise naming for getOclMat function.

---
 modules/core/src/matrix.cpp             | 12 ++++++------
 modules/ocl/include/opencv2/ocl/ocl.hpp |  6 +++---
 modules/ocl/src/matrix_operations.cpp   |  4 ++--
 3 files changed, 11 insertions(+), 11 deletions(-)

diff --git a/modules/core/src/matrix.cpp b/modules/core/src/matrix.cpp
index c4c0041dd9..5a3600b9b3 100644
--- a/modules/core/src/matrix.cpp
+++ b/modules/core/src/matrix.cpp
@@ -982,7 +982,7 @@ Mat _InputArray::getMat(int i) const
 
     if( k == OCL_MAT )
     {
-        CV_Error(-1, "Not implemented");
+        CV_Error(CV_StsNotImplemented, "This method is not implemented for oclMat yet");
     }
 
     CV_Assert( k == STD_VECTOR_MAT );
@@ -1069,7 +1069,7 @@ void _InputArray::getMatVector(vector<Mat>& mv) const
 
     if( k == OCL_MAT )
     {
-        CV_Error(-1, "Not implemented");
+        CV_Error(CV_StsNotImplemented, "This method is not implemented for oclMat yet");
     }
 
     CV_Assert( k == STD_VECTOR_MAT );
@@ -1201,7 +1201,7 @@ Size _InputArray::size(int i) const
 
     if( k == OCL_MAT )
     {
-        CV_Error(-1, "Not implemented");
+        CV_Error(CV_StsNotImplemented, "This method is not implemented for oclMat yet");
     }
 
     CV_Assert( k == GPU_MAT );
@@ -1320,7 +1320,7 @@ bool _InputArray::empty() const
 
     if( k == OCL_MAT )
     {
-        CV_Error(-1, "Not implemented");
+        CV_Error(CV_StsNotImplemented, "This method is not implemented for oclMat yet");
     }
 
     CV_Assert( k == GPU_MAT );
@@ -1545,7 +1545,7 @@ void _OutputArray::create(int dims, const int* sizes, int mtype, int i, bool all
 
     if( k == OCL_MAT )
     {
-        CV_Error(-1, "Not implemented");
+        CV_Error(CV_StsNotImplemented, "This method is not implemented for oclMat yet");
     }
 
     if( k == NONE )
@@ -1661,7 +1661,7 @@ void _OutputArray::release() const
 
     if( k == OCL_MAT )
     {
-        CV_Error(-1, "Not implemented");
+        CV_Error(CV_StsNotImplemented, "This method is not implemented for oclMat yet");
     }
 
     CV_Assert( k == STD_VECTOR_MAT );
diff --git a/modules/ocl/include/opencv2/ocl/ocl.hpp b/modules/ocl/include/opencv2/ocl/ocl.hpp
index 9fdd8f3e99..ed887e61a6 100644
--- a/modules/ocl/include/opencv2/ocl/ocl.hpp
+++ b/modules/ocl/include/opencv2/ocl/ocl.hpp
@@ -392,9 +392,9 @@ namespace cv
             int wholecols;
         };
 
-        // convert InputArray/OutputArray to oclMat
-        CV_EXPORTS oclMat& getOclMat(InputArray src);
-        CV_EXPORTS oclMat& getOclMat(OutputArray src);
+        // convert InputArray/OutputArray to oclMat references
+        CV_EXPORTS oclMat& getOclMatRef(InputArray src);
+        CV_EXPORTS oclMat& getOclMatRef(OutputArray src);
 
         ///////////////////// mat split and merge /////////////////////////////////
         //! Compose a multi-channel array from several single-channel arrays
diff --git a/modules/ocl/src/matrix_operations.cpp b/modules/ocl/src/matrix_operations.cpp
index dc7deebe38..dcaf0418ac 100644
--- a/modules/ocl/src/matrix_operations.cpp
+++ b/modules/ocl/src/matrix_operations.cpp
@@ -244,13 +244,13 @@ cv::ocl::oclMat::operator cv::_OutputArray()
     return newOutputArray;
 }
 
-cv::ocl::oclMat& cv::ocl::getOclMat(InputArray src)
+cv::ocl::oclMat& cv::ocl::getOclMatRef(InputArray src)
 {
     CV_Assert(src.flags & cv::_InputArray::OCL_MAT);
     return *reinterpret_cast<oclMat*>(src.obj);
 }
 
-cv::ocl::oclMat& cv::ocl::getOclMat(OutputArray src)
+cv::ocl::oclMat& cv::ocl::getOclMatRef(OutputArray src)
 {
     CV_Assert(src.flags & cv::_InputArray::OCL_MAT);
     return *reinterpret_cast<oclMat*>(src.obj);