added updateBackgroundModel parameter and release method

modules/video/include/opencv2/video/background_segm.hpp

@@ -221,6 +221,11 @@ public:
      */
     virtual void operator()(InputArray image, OutputArray fgmask, double learningRate=-1.0);
 
+    /**
+     * Releases all inner buffers.
+     */
+    void release();
+
     //! Total number of distinct colors to maintain in histogram.
     int     maxFeatures;
     //! Set between 0.0 and 1.0, determines how quickly features are "forgotten" from histograms.
@@ -231,10 +236,12 @@ public:
     int     quantizationLevels;
     //! Prior probability that any given pixel is a background pixel. A sensitivity parameter.
     double  backgroundPrior;
-    //! value above which pixel is determined to be FG.
+    //! Value above which pixel is determined to be FG.
     double  decisionThreshold;
-    //! smoothing radius, in pixels, for cleaning up FG image.
+    //! Smoothing radius, in pixels, for cleaning up FG image.
     int     smoothingRadius;
+    //! Perform background model update
+    bool updateBackgroundModel;
 
 private:
     double maxVal_;

modules/video/src/bgfg_gmg.cpp

@@ -60,6 +60,7 @@ cv::BackgroundSubtractorGMG::BackgroundSubtractorGMG()
     backgroundPrior = 0.8;
     decisionThreshold = 0.8;
     smoothingRadius = 7;
+    updateBackgroundModel = true;
 }
 
 cv::BackgroundSubtractorGMG::~BackgroundSubtractorGMG()
@@ -199,11 +200,11 @@ namespace
     public:
         GMG_LoopBody(const cv::Mat& frame, const cv::Mat& fgmask, const cv::Mat_<int>& nfeatures, const cv::Mat_<int>& colors, const cv::Mat_<float>& weights,
                      int maxFeatures, double learningRate, int numInitializationFrames, int quantizationLevels, double backgroundPrior, double decisionThreshold,
-                     double maxVal, double minVal, int frameNum) :
+                     double maxVal, double minVal, int frameNum, bool updateBackgroundModel) :
             frame_(frame), fgmask_(fgmask), nfeatures_(nfeatures), colors_(colors), weights_(weights),
             maxFeatures_(maxFeatures), learningRate_(learningRate), numInitializationFrames_(numInitializationFrames),
             quantizationLevels_(quantizationLevels), backgroundPrior_(backgroundPrior), decisionThreshold_(decisionThreshold),
-            maxVal_(maxVal), minVal_(minVal), frameNum_(frameNum)
+            maxVal_(maxVal), minVal_(minVal), frameNum_(frameNum), updateBackgroundModel_(updateBackgroundModel)
         {
         }
 
@@ -224,6 +225,7 @@ namespace
         int     quantizationLevels_;
         double  backgroundPrior_;
         double  decisionThreshold_;
+        bool updateBackgroundModel_;
 
         double maxVal_;
         double minVal_;
@@ -275,18 +277,21 @@ namespace
 
                     // update histogram.
 
-                    for (int i = 0; i < nfeatures; ++i)
-                        weights[i] *= 1.0f - learningRate_;
+                    if (updateBackgroundModel_)
+                    {
+                        for (int i = 0; i < nfeatures; ++i)
+                            weights[i] *= 1.0f - learningRate_;
 
-                    bool inserted = insertFeature(newFeatureColor, learningRate_, colors, weights, nfeatures, maxFeatures_);
+                        bool inserted = insertFeature(newFeatureColor, learningRate_, colors, weights, nfeatures, maxFeatures_);
 
-                    if (inserted)
-                    {
-                        normalizeHistogram(weights, nfeatures);
-                        nfeatures_row[x] = nfeatures;
+                        if (inserted)
+                        {
+                            normalizeHistogram(weights, nfeatures);
+                            nfeatures_row[x] = nfeatures;
+                        }
                     }
                 }
-                else
+                else if (updateBackgroundModel_)
                 {
                     // training-mode update
 
@@ -323,12 +328,25 @@ void cv::BackgroundSubtractorGMG::operator ()(InputArray _frame, OutputArray _fg
 
     GMG_LoopBody body(frame, fgmask, nfeatures_, colors_, weights_,
                       maxFeatures, learningRate, numInitializationFrames, quantizationLevels, backgroundPrior, decisionThreshold,
-                      maxVal_, minVal_, frameNum_);
+                      maxVal_, minVal_, frameNum_, updateBackgroundModel);
     cv::parallel_for_(cv::Range(0, frame.rows), body);
 
-    cv::medianBlur(fgmask, buf_, smoothingRadius);
-    cv::swap(fgmask, buf_);
+    if (smoothingRadius > 0)
+    {
+        cv::medianBlur(fgmask, buf_, smoothingRadius);
+        cv::swap(fgmask, buf_);
+    }
 
     // keep track of how many frames we have processed
     ++frameNum_;
 }
+
+void cv::BackgroundSubtractorGMG::release()
+{
+    frameSize_ = cv::Size();
+
+    nfeatures_.release();
+    colors_.release();
+    weights_.release();
+    buf_.release();
+}

modules/video/src/video_init.cpp

@@ -78,7 +78,9 @@ CV_INIT_ALGORITHM(BackgroundSubtractorGMG, "BackgroundSubtractor.GMG",
                   obj.info()->addParam(obj, "smoothingRadius", obj.smoothingRadius,false,0,0,
                                        "Radius of smoothing kernel to filter noise from FG mask image.");
                   obj.info()->addParam(obj, "decisionThreshold", obj.decisionThreshold,false,0,0,
-                                       "Threshold for FG decision rule. Pixel is FG if posterior probability exceeds threshold."));
+                                       "Threshold for FG decision rule. Pixel is FG if posterior probability exceeds threshold.");
+                  obj.info()->addParam(obj, "updateBackgroundModel", obj.updateBackgroundModel,false,0,0,
+                                       "Perform background model update."));
 
 bool initModule_video(void)
 {