Base class for background/foreground segmentation. : More...

#include <opencv2/video/background_segm.hpp>

Inheritance diagram for cv::BackgroundSubtractor:

Public Member Functions
virtual void	apply (InputArray image, OutputArray fgmask, double learningRate=-1)=0
	Computes a foreground mask.

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

virtual void	write (FileStorage &fs) const
	Stores algorithm parameters in a file storage.

void	write (const Ptr< FileStorage > &fs, const String &name=String()) const
	simplified API for language bindingsThis is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

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

Base class for background/foreground segmentation. :

The class is only used to define the common interface for the whole family of background/foreground segmentation algorithms.

Member Function Documentation

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

pure virtual

Python:
	fgmask	=	cv.BackgroundSubtractor.apply(	image[, fgmask[, learningRate]]	)

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.

virtual void cv::BackgroundSubtractor::getBackgroundImage ( OutputArray backgroundImage ) const

pure virtual

Python:
	backgroundImage	=	cv.BackgroundSubtractor.getBackgroundImage(	[, 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.

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