refactored MOG2 algorithm

modules/gpubgsegm/include/opencv2/gpubgsegm.hpp

@@ -73,6 +73,27 @@ CV_EXPORTS Ptr<gpu::BackgroundSubtractorMOG>
     createBackgroundSubtractorMOG(int history = 200, int nmixtures = 5,
                                   double backgroundRatio = 0.7, double noiseSigma = 0);
 
+////////////////////////////////////////////////////
+// MOG2
+
+class CV_EXPORTS BackgroundSubtractorMOG2 : public cv::BackgroundSubtractorMOG2
+{
+public:
+    using cv::BackgroundSubtractorMOG2::apply;
+    using cv::BackgroundSubtractorMOG2::getBackgroundImage;
+
+    virtual void apply(InputArray image, OutputArray fgmask, double learningRate, Stream& stream) = 0;
+
+    virtual void getBackgroundImage(OutputArray backgroundImage, Stream& stream) const = 0;
+};
+
+CV_EXPORTS Ptr<gpu::BackgroundSubtractorMOG2>
+    createBackgroundSubtractorMOG2(int history = 500, double varThreshold = 16,
+                                   bool detectShadows = true);
+
+
+
+
 
 
 
@@ -140,99 +161,6 @@ private:
     std::auto_ptr<Impl> impl_;
 };
 
-/*!
- The class implements the following algorithm:
- "Improved adaptive Gausian mixture model for background subtraction"
- Z.Zivkovic
- International Conference Pattern Recognition, UK, August, 2004.
- http://www.zoranz.net/Publications/zivkovic2004ICPR.pdf
-*/
-class CV_EXPORTS MOG2_GPU
-{
-public:
-    //! the default constructor
-    MOG2_GPU(int nmixtures = -1);
-
-    //! re-initiaization method
-    void initialize(Size frameSize, int frameType);
-
-    //! the update operator
-    void operator()(const GpuMat& frame, GpuMat& fgmask, float learningRate = -1.0f, Stream& stream = Stream::Null());
-
-    //! computes a background image which are the mean of all background gaussians
-    void getBackgroundImage(GpuMat& backgroundImage, Stream& stream = Stream::Null()) const;
-
-    //! releases all inner buffers
-    void release();
-
-    // parameters
-    // you should call initialize after parameters changes
-
-    int history;
-
-    //! here it is the maximum allowed number of mixture components.
-    //! Actual number is determined dynamically per pixel
-    float varThreshold;
-    // threshold on the squared Mahalanobis distance to decide if it is well described
-    // by the background model or not. Related to Cthr from the paper.
-    // This does not influence the update of the background. A typical value could be 4 sigma
-    // and that is varThreshold=4*4=16; Corresponds to Tb in the paper.
-
-    /////////////////////////
-    // less important parameters - things you might change but be carefull
-    ////////////////////////
-
-    float backgroundRatio;
-    // corresponds to fTB=1-cf from the paper
-    // TB - threshold when the component becomes significant enough to be included into
-    // the background model. It is the TB=1-cf from the paper. So I use cf=0.1 => TB=0.
-    // For alpha=0.001 it means that the mode should exist for approximately 105 frames before
-    // it is considered foreground
-    // float noiseSigma;
-    float varThresholdGen;
-
-    //correspondts to Tg - threshold on the squared Mahalan. dist. to decide
-    //when a sample is close to the existing components. If it is not close
-    //to any a new component will be generated. I use 3 sigma => Tg=3*3=9.
-    //Smaller Tg leads to more generated components and higher Tg might make
-    //lead to small number of components but they can grow too large
-    float fVarInit;
-    float fVarMin;
-    float fVarMax;
-
-    //initial variance  for the newly generated components.
-    //It will will influence the speed of adaptation. A good guess should be made.
-    //A simple way is to estimate the typical standard deviation from the images.
-    //I used here 10 as a reasonable value
-    // min and max can be used to further control the variance
-    float fCT; //CT - complexity reduction prior
-    //this is related to the number of samples needed to accept that a component
-    //actually exists. We use CT=0.05 of all the samples. By setting CT=0 you get
-    //the standard Stauffer&Grimson algorithm (maybe not exact but very similar)
-
-    //shadow detection parameters
-    bool bShadowDetection; //default 1 - do shadow detection
-    unsigned char nShadowDetection; //do shadow detection - insert this value as the detection result - 127 default value
-    float fTau;
-    // Tau - shadow threshold. The shadow is detected if the pixel is darker
-    //version of the background. Tau is a threshold on how much darker the shadow can be.
-    //Tau= 0.5 means that if pixel is more than 2 times darker then it is not shadow
-    //See: Prati,Mikic,Trivedi,Cucchiarra,"Detecting Moving Shadows...",IEEE PAMI,2003.
-
-private:
-    int nmixtures_;
-
-    Size frameSize_;
-    int frameType_;
-    int nframes_;
-
-    GpuMat weight_;
-    GpuMat variance_;
-    GpuMat mean_;
-
-    GpuMat bgmodelUsedModes_; //keep track of number of modes per pixel
-};
-
 /**
  * Background Subtractor module. Takes a series of images and returns a sequence of mask (8UC1)
  * images of the same size, where 255 indicates Foreground and 0 represents Background.