cv::bgsegm::BackgroundSubtractorGSOC Class Reference

Implementation of the different yet better algorithm which is called GSOC, as it was implemented during GSOC and was not originated from any paper. More...

#include <opencv2/bgsegm.hpp>

Collaboration diagram for cv::bgsegm::BackgroundSubtractorGSOC:

Public Member Functions
virtual void	apply (InputArray image, OutputArray fgmask, double learningRate=-1) CV_OVERRIDE=0
	Computes a foreground mask.
virtual void	getBackgroundImage (OutputArray backgroundImage) const CV_OVERRIDE=0
	Computes a background image.
Public Member Functions inherited from cv::BackgroundSubtractor
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

Implementation of the different yet better algorithm which is called GSOC, as it was implemented during GSOC and was not originated from any paper.

This algorithm demonstrates better performance on CDNET 2014 dataset compared to other algorithms in OpenCV.

Member Function Documentation

apply()

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

pure virtual

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

Computes a foreground mask.

Parameters

image	Next video frame.
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.

getBackgroundImage()

virtual void cv::bgsegm::BackgroundSubtractorGSOC::getBackgroundImage ( OutputArray backgroundImage ) const

pure virtual

Python:
	cv.bgsegm.BackgroundSubtractorGSOC.getBackgroundImage(	[, backgroundImage]	) ->	backgroundImage

Computes a background image.

Parameters

backgroundImage

The output background image.

Note

Sometimes the background image can be very blurry, as it contain the average background statistics.

Implements cv::BackgroundSubtractor.

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

• opencv2/bgsegm.hpp