cv::bgsegm::BackgroundSubtractorMOG Class Reference

Gaussian Mixture-based Background/Foreground Segmentation Algorithm. More...

#include <opencv2/bgsegm.hpp>

Collaboration diagram for cv::bgsegm::BackgroundSubtractorMOG:

Public Member Functions
virtual void	apply (InputArray image, InputArray knownForegroundMask, OutputArray fgmask, double learningRate=-1) CV_OVERRIDE=0
	Computes a foreground mask and skips known foreground in evaluation.
virtual void	apply (InputArray image, OutputArray fgmask, double learningRate=-1) CV_OVERRIDE=0
	Computes a foreground mask.
virtual double	getBackgroundRatio () const =0
virtual int	getHistory () const =0
virtual int	getNMixtures () const =0
virtual double	getNoiseSigma () const =0
virtual void	setBackgroundRatio (double backgroundRatio)=0
virtual void	setHistory (int nframes)=0
virtual void	setNMixtures (int nmix)=0
virtual void	setNoiseSigma (double noiseSigma)=0
Public Member Functions inherited from cv::BackgroundSubtractor
virtual void	getBackgroundImage (OutputArray backgroundImage) const =0
	Computes a background image.
Public Member Functions inherited from cv::Algorithm
	Algorithm ()
virtual	~Algorithm ()
virtual void	clear ()
	Clears the algorithm state.
virtual bool	empty () const
	Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read.
virtual String	getDefaultName () const
virtual void	read (const FileNode &fn)
	Reads algorithm parameters from a file storage.
virtual void	save (const String &filename) const
void	write (const Ptr< FileStorage > &fs, const String &name=String()) const
virtual void	write (FileStorage &fs) const
	Stores algorithm parameters in a file storage.
void	write (FileStorage &fs, const String &name) const

Additional Inherited Members
Static Public Member Functions inherited from cv::Algorithm
template<typename _Tp >
static Ptr< _Tp >	load (const String &filename, const String &objname=String())
	Loads algorithm from the file.
template<typename _Tp >
static Ptr< _Tp >	loadFromString (const String &strModel, const String &objname=String())
	Loads algorithm from a String.
template<typename _Tp >
static Ptr< _Tp >	read (const FileNode &fn)
	Reads algorithm from the file node.
Protected Member Functions inherited from cv::Algorithm
void	writeFormat (FileStorage &fs) const

Detailed Description

Gaussian Mixture-based Background/Foreground Segmentation Algorithm.

The class implements the algorithm described in [141] .

Member Function Documentation

apply() [1/2]

virtual void cv::bgsegm::BackgroundSubtractorMOG::apply ( InputArray image, InputArray knownForegroundMask, OutputArray fgmask, double learningRate = -1 )

pure virtual

Python:
	cv.bgsegm.BackgroundSubtractorMOG.apply(	image[, fgmask[, learningRate]]	) ->	fgmask
	cv.bgsegm.BackgroundSubtractorMOG.apply(	image, knownForegroundMask[, fgmask[, learningRate]]	) ->	fgmask

Computes a foreground mask and skips known foreground in evaluation.

Parameters

image	Next video frame of type CV_8UC(n),CV_8SC(n),CV_16UC(n),CV_16SC(n),CV_32SC(n),CV_32FC(n),CV_64FC(n), where n is 1,2,3,4.
fgmask	The output foreground mask as an 8-bit binary image.
knownForegroundMask	The mask for inputting already known foreground, allows model to ignore learning known pixels.
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.

Implements cv::BackgroundSubtractor.

apply() [2/2]

virtual void cv::bgsegm::BackgroundSubtractorMOG::apply ( InputArray image, OutputArray fgmask, double learningRate = -1 )

pure virtual

Python:
	cv.bgsegm.BackgroundSubtractorMOG.apply(	image[, fgmask[, learningRate]]	) ->	fgmask
	cv.bgsegm.BackgroundSubtractorMOG.apply(	image, knownForegroundMask[, fgmask[, learningRate]]	) ->	fgmask

Computes a foreground mask.

Parameters

image	Next video frame of type CV_8UC(n),CV_8SC(n),CV_16UC(n),CV_16SC(n),CV_32SC(n),CV_32FC(n),CV_64FC(n), where n is 1,2,3,4.
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.

Implements cv::BackgroundSubtractor.

getBackgroundRatio()

virtual double cv::bgsegm::BackgroundSubtractorMOG::getBackgroundRatio ( ) const

pure virtual

Python:
	cv.bgsegm.BackgroundSubtractorMOG.getBackgroundRatio(		) ->	retval

getHistory()

virtual int cv::bgsegm::BackgroundSubtractorMOG::getHistory ( ) const

pure virtual

Python:
	cv.bgsegm.BackgroundSubtractorMOG.getHistory(		) ->	retval

getNMixtures()

virtual int cv::bgsegm::BackgroundSubtractorMOG::getNMixtures ( ) const

pure virtual

Python:
	cv.bgsegm.BackgroundSubtractorMOG.getNMixtures(		) ->	retval

getNoiseSigma()

virtual double cv::bgsegm::BackgroundSubtractorMOG::getNoiseSigma ( ) const

pure virtual

Python:
	cv.bgsegm.BackgroundSubtractorMOG.getNoiseSigma(		) ->	retval

setBackgroundRatio()

virtual void cv::bgsegm::BackgroundSubtractorMOG::setBackgroundRatio ( double backgroundRatio )

pure virtual

Python:
	cv.bgsegm.BackgroundSubtractorMOG.setBackgroundRatio(	backgroundRatio	) ->	None

setHistory()

virtual void cv::bgsegm::BackgroundSubtractorMOG::setHistory ( int nframes )

pure virtual

Python:
	cv.bgsegm.BackgroundSubtractorMOG.setHistory(	nframes	) ->	None

setNMixtures()

virtual void cv::bgsegm::BackgroundSubtractorMOG::setNMixtures ( int nmix )

pure virtual

Python:
	cv.bgsegm.BackgroundSubtractorMOG.setNMixtures(	nmix	) ->	None

setNoiseSigma()

virtual void cv::bgsegm::BackgroundSubtractorMOG::setNoiseSigma ( double noiseSigma )

pure virtual

Python:
	cv.bgsegm.BackgroundSubtractorMOG.setNoiseSigma(	noiseSigma	) ->	None

---

The documentation for this class was generated from the following file:

• opencv2/bgsegm.hpp