tracking: eliminate code duplication

modules/tracking/src/tldDetector.cpp

@@ -40,6 +40,7 @@
 //M*/
 
 #include "tldDetector.hpp"
+#include "tracking_utils.hpp"
 
 #include <opencv2/core/utility.hpp>
 
@@ -72,12 +73,12 @@ namespace cv
 			for (int i = 0; i < *posNum; i++)
 			{
 				modelSample.data = &(posExp->data[i * 225]);
-				splus = std::max(splus, 0.5 * (NCC(modelSample, patch) + 1.0));
+                splus = std::max(splus, 0.5 * (tracking_internal::computeNCC(modelSample, patch) + 1.0));
 			}
 			for (int i = 0; i < *negNum; i++)
 			{
 				modelSample.data = &(negExp->data[i * 225]);
-				sminus = std::max(sminus, 0.5 * (NCC(modelSample, patch) + 1.0));
+                sminus = std::max(sminus, 0.5 * (tracking_internal::computeNCC(modelSample, patch) + 1.0));
 			}
 
 			if (splus + sminus == 0.0)
@@ -167,7 +168,7 @@ namespace cv
 			for (int id = 0; id < numOfPatches; id++)
 			{
 				double spr = 0.0, smr = 0.0, spc = 0.0, smc = 0;
-				int med = getMedian((*timeStampsPositive));
+                int med = tracking_internal::getMedian((*timeStampsPositive));
 				for (int i = 0; i < *posNum; i++)
 				{
 					spr = std::max(spr, 0.5 * (posNCC.at<float>(id * 500 + i) + 1.0));
@@ -195,19 +196,19 @@ namespace cv
 		{
 			double splus = 0.0, sminus = 0.0;
 			Mat_<uchar> modelSample(STANDARD_PATCH_SIZE, STANDARD_PATCH_SIZE);
-			int med = getMedian((*timeStampsPositive));
+            int med = tracking_internal::getMedian((*timeStampsPositive));
 			for (int i = 0; i < *posNum; i++)
 			{
 				if ((int)(*timeStampsPositive)[i] <= med)
 				{
 					modelSample.data = &(posExp->data[i * 225]);
-					splus = std::max(splus, 0.5 * (NCC(modelSample, patch) + 1.0));
+                    splus = std::max(splus, 0.5 * (tracking_internal::computeNCC(modelSample, patch) + 1.0));
 				}
 			}
 			for (int i = 0; i < *negNum; i++)
 			{
 				modelSample.data = &(negExp->data[i * 225]);
-				sminus = std::max(sminus, 0.5 * (NCC(modelSample, patch) + 1.0));
+                sminus = std::max(sminus, 0.5 * (tracking_internal::computeNCC(modelSample, patch) + 1.0));
 			}
 
 			if (splus + sminus == 0.0)
@@ -249,7 +250,7 @@ namespace cv
 
 			Mat resNCC = devNCC.getMat(ACCESS_READ);
 
-			int med = getMedian((*timeStampsPositive));
+            int med = tracking_internal::getMedian((*timeStampsPositive));
 			for (int i = 0; i < *posNum; i++)
 				if ((int)(*timeStampsPositive)[i] <= med)
 					splus = std::max(splus, 0.5 * (resNCC.at<float>(i) +1.0));

modules/tracking/src/tldUtils.cpp

@@ -164,35 +164,6 @@ double variance(const Mat& img)
     return p2 - p * p;
 }
 
-//Normalized Correlation Coefficient
-double NCC(const Mat_<uchar>& patch1, const Mat_<uchar>& patch2)
-{
-    CV_Assert( patch1.rows == patch2.rows );
-    CV_Assert( patch1.cols == patch2.cols );
-
-    int N = patch1.rows * patch1.cols;
-    double s1 = sum(patch1)(0);
-    double s2 = sum(patch2)(0);
-    double n1 = norm(patch1, NORM_L2SQR);
-    double n2 = norm(patch2, NORM_L2SQR);
-    double prod=patch1.dot(patch2);
-    double sq1 = sqrt(std::max(0.0, n1 - 1.0 * s1 * s1 / N));
-    double sq2 = sqrt(std::max(0.0, n2 - 1.0 * s2 * s2 / N));
-    return (sq2 == 0) ? sq1 / abs(sq1) : (prod - s1 * s2 / N) / sq1 / sq2;
-}
-
-int getMedian(const std::vector<int>& values, int size)
-{
-    if( size == -1 )
-        size = (int)values.size();
-    std::vector<int> copy(values.begin(), values.begin() + size);
-    std::sort(copy.begin(), copy.end());
-    if( size % 2 == 0 )
-        return (copy[size / 2 - 1] + copy[size / 2]) / 2;
-    else
-        return copy[(size - 1) / 2];
-}
-
 //Overlap between two BB
 double overlap(const Rect2d& r1, const Rect2d& r2)
 {

modules/tracking/src/tldUtils.hpp

@@ -46,13 +46,8 @@ namespace cv
 		void resample(const Mat& img, const Rect2d& r2, Mat_<uchar>& samples);
 		/** Computes the variance of single given image.*/
 		double variance(const Mat& img);
-		/** Computes normalized corellation coefficient between the two patches (they should be
-		* of the same size).*/
-		double NCC(const Mat_<uchar>& patch1, const Mat_<uchar>& patch2);
 		void getClosestN(std::vector<Rect2d>& scanGrid, Rect2d bBox, int n, std::vector<Rect2d>& res);
 		double scaleAndBlur(const Mat& originalImg, int scale, Mat& scaledImg, Mat& blurredImg, Size GaussBlurKernelSize, double scaleStep);
-		int getMedian(const std::vector<int>& values, int size = -1);
-
 	}
 }
 

modules/tracking/src/trackerMedianFlow.cpp

@@ -42,6 +42,7 @@
 #include "precomp.hpp"
 #include "opencv2/video/tracking.hpp"
 #include "opencv2/imgproc.hpp"
+#include "tracking_utils.hpp"
 #include <algorithm>
 #include <limits.h>
 
@@ -94,12 +95,6 @@ private:
     TrackerMedianFlow::Params params;
 };
 
-template<typename T>
-T getMedian( const std::vector<T>& values );
-
-template<typename T>
-T getMedianAndDoPartition( std::vector<T>& values );
-
 Mat getPatch(Mat image, Size patch_size, Point2f patch_center)
 {
     Mat patch;
@@ -282,7 +277,7 @@ bool TrackerMedianFlowImpl::medianFlowImpl(Mat oldImage,Mat newImage,Rect2d& old
         di[i]-=mDisplacement;
         displacements.push_back((float)sqrt(di[i].ddot(di[i])));
     }
-    float median_displacements = getMedianAndDoPartition(displacements);
+    float median_displacements = tracking_internal::getMedianAndDoPartition(displacements);
     dprintf(("\tmedian of length of difference of displacements = %f\n", median_displacements));
     if(median_displacements > params.maxMedianLengthOfDisplacementDifference){
         dprintf(("\tmedian flow tracker returns false due to big median length of difference between displacements\n"));
@@ -310,10 +305,10 @@ Rect2d TrackerMedianFlowImpl::vote(const std::vector<Point2f>& oldPoints,const s
     float xshift=0,yshift=0;
     std::vector<float> buf_for_location(n, 0.);
     for(size_t i=0;i<n;i++){  buf_for_location[i]=newPoints[i].x-oldPoints[i].x;  }
-    xshift=getMedianAndDoPartition(buf_for_location);
+    xshift=tracking_internal::getMedianAndDoPartition(buf_for_location);
     newCenter.x+=xshift;
     for(size_t i=0;i<n;i++){  buf_for_location[i]=newPoints[i].y-oldPoints[i].y;  }
-    yshift=getMedianAndDoPartition(buf_for_location);
+    yshift=tracking_internal::getMedianAndDoPartition(buf_for_location);
     newCenter.y+=yshift;
     mD=Point2f((float)xshift,(float)yshift);
 
@@ -327,7 +322,7 @@ Rect2d TrackerMedianFlowImpl::vote(const std::vector<Point2f>& oldPoints,const s
         }
     }
 
-    double scale=getMedianAndDoPartition(buf_for_scale);
+    double scale=tracking_internal::getMedianAndDoPartition(buf_for_scale);
     dprintf(("xshift, yshift, scale = %f %f %f\n",xshift,yshift,scale));
     newRect.x=newCenter.x-scale*oldRect.width/2.0;
     newRect.y=newCenter.y-scale*oldRect.height/2.0;
@@ -371,7 +366,7 @@ void TrackerMedianFlowImpl::check_FB(const std::vector<Mat>& oldImagePyr, const
     for(size_t i=0;i<oldPoints.size();i++){
         FBerror[i]=(float)norm(oldPoints[i]-pointsToTrackReprojection[i]);
     }
-    float FBerrorMedian=getMedian(FBerror);
+    float FBerrorMedian=tracking_internal::getMedian(FBerror);
     dprintf(("point median=%f\n",FBerrorMedian));
     dprintf(("FBerrorMedian=%f\n",FBerrorMedian));
     for(size_t i=0;i<oldPoints.size();i++){
@@ -388,51 +383,14 @@ void TrackerMedianFlowImpl::check_NCC(const Mat& oldImage,const Mat& newImage,
         p1 = getPatch(oldImage, params.winSizeNCC, oldPoints[i]);
         p2 = getPatch(newImage, params.winSizeNCC, newPoints[i]);
 
-        const int patch_area=params.winSizeNCC.area();
-        double s1=sum(p1)(0),s2=sum(p2)(0);
-        double n1=norm(p1),n2=norm(p2);
-        double prod=p1.dot(p2);
-        double sq1=sqrt(n1*n1-s1*s1/patch_area),sq2=sqrt(n2*n2-s2*s2/patch_area);
-        double ares=(sq2==0)?sq1/abs(sq1):(prod-s1*s2/patch_area)/sq1/sq2;
-
-        NCC[i] = (float)ares;
+        NCC[i] = (float)tracking_internal::computeNCC(p1, p2);
     }
-    float median = getMedian(NCC);
+    float median = tracking_internal::getMedian(NCC);
     for(size_t i = 0; i < oldPoints.size(); i++) {
         status[i] = status[i] && (NCC[i] >= median);
     }
 }
 
-template<typename T>
-T getMedian(const std::vector<T>& values)
-{
-    std::vector<T> copy(values);
-    return getMedianAndDoPartition(copy);
-}
-
-template<typename T>
-T getMedianAndDoPartition(std::vector<T>& values)
-{
-    size_t size = values.size();
-    if(size%2==0)
-    {
-        std::nth_element(values.begin(), values.begin() + size/2-1, values.end());
-        T firstMedian = values[size/2-1];
-
-        std::nth_element(values.begin(), values.begin() + size/2, values.end());
-        T secondMedian = values[size/2];
-
-        return (firstMedian + secondMedian) / (T)2;
-    }
-    else
-    {
-        size_t medianIndex = (size - 1) / 2;
-        std::nth_element(values.begin(), values.begin() + medianIndex, values.end());
-
-        return values[medianIndex];
-    }
-}
-
 } /* anonymous namespace */
 
 namespace cv

modules/tracking/src/tracking_utils.cpp

@@ -0,0 +1,23 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html.
+
+#include "tracking_utils.hpp"
+
+using namespace cv;
+
+double tracking_internal::computeNCC(const Mat& patch1, const Mat& patch2)
+{
+    CV_Assert( patch1.rows == patch2.rows );
+    CV_Assert( patch1.cols == patch2.cols );
+
+    int N = patch1.rows * patch1.cols;
+    double s1 = sum(patch1)(0);
+    double s2 = sum(patch2)(0);
+    double n1 = norm(patch1, NORM_L2SQR);
+    double n2 = norm(patch2, NORM_L2SQR);
+    double prod=patch1.dot(patch2);
+    double sq1 = sqrt(std::max(0.0, n1 - 1.0 * s1 * s1 / N));
+    double sq2 = sqrt(std::max(0.0, n2 - 1.0 * s2 * s2 / N));
+    return (sq2 == 0) ? sq1 / abs(sq1) : (prod - s1 * s2 / N) / sq1 / sq2;
+}

modules/tracking/src/tracking_utils.hpp

@@ -0,0 +1,47 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html.
+#ifndef __OPENCV_TRACKING_UTILS_HPP__
+
+#include "precomp.hpp"
+#include <algorithm>
+
+namespace cv {
+namespace tracking_internal
+{
+/** Computes normalized corellation coefficient between the two patches (they should be
+* of the same size).*/
+    double computeNCC(const Mat& patch1, const Mat& patch2);
+
+    template<typename T>
+    T getMedianAndDoPartition(std::vector<T>& values)
+    {
+        size_t size = values.size();
+        if(size%2==0)
+        {
+            std::nth_element(values.begin(), values.begin() + size/2-1, values.end());
+            T firstMedian = values[size/2-1];
+
+            std::nth_element(values.begin(), values.begin() + size/2, values.end());
+            T secondMedian = values[size/2];
+
+            return (firstMedian + secondMedian) / (T)2;
+        }
+        else
+        {
+            size_t medianIndex = (size - 1) / 2;
+            std::nth_element(values.begin(), values.begin() + medianIndex, values.end());
+
+            return values[medianIndex];
+        }
+    }
+
+    template<typename T>
+    T getMedian(const std::vector<T>& values)
+    {
+        std::vector<T> copy(values);
+        return getMedianAndDoPartition(copy);
+    }
+}
+}
+#endif