class cv::BackgroundSubtractorMOG2
Overview
Gaussian Mixture-based Background/Foreground Segmentation Algorithm. More…
#include <background_segm.hpp> class BackgroundSubtractorMOG2: public cv::BackgroundSubtractor { public: // methods virtual void apply( InputArray image, OutputArray fgmask, double learningRate = -1 ) = 0; virtual double getBackgroundRatio() const = 0; virtual double getComplexityReductionThreshold() const = 0; virtual bool getDetectShadows() const = 0; virtual int getHistory() const = 0; virtual int getNMixtures() const = 0; virtual double getShadowThreshold() const = 0; virtual int getShadowValue() const = 0; virtual double getVarInit() const = 0; virtual double getVarMax() const = 0; virtual double getVarMin() const = 0; virtual double getVarThreshold() const = 0; virtual double getVarThresholdGen() const = 0; virtual void setBackgroundRatio(double ratio) = 0; virtual void setComplexityReductionThreshold(double ct) = 0; virtual void setDetectShadows(bool detectShadows) = 0; virtual void setHistory(int history) = 0; virtual void setNMixtures(int nmixtures) = 0; virtual void setShadowThreshold(double threshold) = 0; virtual void setShadowValue(int value) = 0; virtual void setVarInit(double varInit) = 0; virtual void setVarMax(double varMax) = 0; virtual void setVarMin(double varMin) = 0; virtual void setVarThreshold(double varThreshold) = 0; virtual void setVarThresholdGen(double varThresholdGen) = 0; }; // direct descendants class BackgroundSubtractorMOG2;
Inherited Members
public: // methods virtual void clear(); virtual bool empty() const; virtual String getDefaultName() const; virtual void read(const FileNode& fn); virtual void save(const String& filename) const; virtual void write(FileStorage& fs) const; template <typename _Tp> static Ptr<_Tp> load( const String& filename, const String& objname = String() ); template <typename _Tp> static Ptr<_Tp> loadFromString( const String& strModel, const String& objname = String() ); template <typename _Tp> static Ptr<_Tp> read(const FileNode& fn); virtual void apply( InputArray image, OutputArray fgmask, double learningRate = -1 ) = 0; virtual void getBackgroundImage(OutputArray backgroundImage) const = 0; protected: // methods void writeFormat(FileStorage& fs) const;
Detailed Documentation
Gaussian Mixture-based Background/Foreground Segmentation Algorithm.
The class implements the Gaussian mixture model background subtraction described in [98] and [97].
Methods
virtual void apply( InputArray image, OutputArray fgmask, double learningRate = -1 ) = 0
Computes a foreground mask.
Parameters:
| image | Next video frame. Floating point frame will be used without scaling and should be in range \([0,255]\). |
| fgmask | The output foreground mask as an 8-bit binary image. |
| learningRate | The value between 0 and 1 that indicates how fast the background model is learnt. Negative parameter value makes the algorithm to use some automatically chosen learning rate. 0 means that the background model is not updated at all, 1 means that the background model is completely reinitialized from the last frame. |
virtual double getBackgroundRatio() const = 0
Returns the “background ratio” parameter of the algorithm.
If a foreground pixel keeps semi-constant value for about backgroundRatio*history frames, it’s considered background and added to the model as a center of a new component. It corresponds to TB parameter in the paper.
virtual double getComplexityReductionThreshold() const = 0
Returns the complexity reduction threshold.
This parameter defines the number of samples needed to accept to prove the component exists. CT=0.05 is a default value for all the samples. By setting CT=0 you get an algorithm very similar to the standard Stauffer&Grimson algorithm.
virtual bool getDetectShadows() const = 0
Returns the shadow detection flag.
If true, the algorithm detects shadows and marks them. See createBackgroundSubtractorMOG2 for details.
virtual int getHistory() const = 0
Returns the number of last frames that affect the background model.
virtual int getNMixtures() const = 0
Returns the number of gaussian components in the background model.
virtual double getShadowThreshold() const = 0
Returns the shadow threshold.
A shadow is detected if pixel is a darker version of the background. The shadow threshold (Tau in the paper) is a threshold defining how much darker the shadow can be. Tau= 0.5 means that if a pixel is more than twice darker then it is not shadow. See Prati, Mikic, Trivedi and Cucchiara, Detecting Moving Shadows…*, IEEE PAMI,2003.
virtual int getShadowValue() const = 0
Returns the shadow value.
Shadow value is the value used to mark shadows in the foreground mask. Default value is 127. Value 0 in the mask always means background, 255 means foreground.
virtual double getVarInit() const = 0
Returns the initial variance of each gaussian component.
virtual double getVarThreshold() const = 0
Returns the variance threshold for the pixel-model match.
The main threshold on the squared Mahalanobis distance to decide if the sample is well described by the background model or not. Related to Cthr from the paper.
virtual double getVarThresholdGen() const = 0
Returns the variance threshold for the pixel-model match used for new mixture component generation.
Threshold for the squared Mahalanobis distance that helps decide when a sample is close to the existing components (corresponds to Tg in the paper). If a pixel is not close to any component, it is considered foreground or added as a new component. 3 sigma => Tg=3*3=9 is default. A smaller Tg value generates more components. A higher Tg value may result in a small number of components but they can grow too large.
virtual void setBackgroundRatio(double ratio) = 0
Sets the “background ratio” parameter of the algorithm.
virtual void setComplexityReductionThreshold(double ct) = 0
Sets the complexity reduction threshold.
virtual void setDetectShadows(bool detectShadows) = 0
Enables or disables shadow detection.
virtual void setHistory(int history) = 0
Sets the number of last frames that affect the background model.
virtual void setNMixtures(int nmixtures) = 0
Sets the number of gaussian components in the background model.
The model needs to be reinitalized to reserve memory.
virtual void setShadowThreshold(double threshold) = 0
Sets the shadow threshold.
virtual void setShadowValue(int value) = 0
Sets the shadow value.
virtual void setVarInit(double varInit) = 0
Sets the initial variance of each gaussian component.
virtual void setVarThreshold(double varThreshold) = 0
Sets the variance threshold for the pixel-model match.
virtual void setVarThresholdGen(double varThresholdGen) = 0
Sets the variance threshold for the pixel-model match used for new mixture component generation.