OpenCV 5.0.0-pre
Open Source Computer Vision
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cv::BackgroundSubtractor Class Referenceabstract

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

#include <opencv2/video/background_segm.hpp>

Collaboration 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 (FileStorage &fs, const String &name) const
 

Additional Inherited Members

- Static Public Member Functions inherited from cv::Algorithm
template<typename _Tp >
static Ptr< _Tpload (const String &filename, const String &objname=String())
 Loads algorithm from the file.
 
template<typename _Tp >
static Ptr< _TploadFromString (const String &strModel, const String &objname=String())
 Loads algorithm from a String.
 
template<typename _Tp >
static Ptr< _Tpread (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

◆ apply()

virtual void cv::BackgroundSubtractor::apply ( InputArray image,
OutputArray fgmask,
double learningRate = -1 )
pure virtual
Python:
cv.BackgroundSubtractor.apply(image[, fgmask[, learningRate]]) -> fgmask

Computes a foreground mask.

Parameters
imageNext video frame.
fgmaskThe output foreground mask as an 8-bit binary image.
learningRateThe 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.

Implemented in cv::BackgroundSubtractorMOG2, cv::bgsegm::BackgroundSubtractorCNT, cv::bgsegm::BackgroundSubtractorGMG, cv::bgsegm::BackgroundSubtractorGSOC, and cv::bgsegm::BackgroundSubtractorLSBP.

◆ getBackgroundImage()

virtual void cv::BackgroundSubtractor::getBackgroundImage ( OutputArray backgroundImage) const
pure virtual
Python:
cv.BackgroundSubtractor.getBackgroundImage([, backgroundImage]) -> backgroundImage

Computes a background image.

Parameters
backgroundImageThe output background image.
Note
Sometimes the background image can be very blurry, as it contain the average background statistics.

Implemented in cv::bgsegm::BackgroundSubtractorCNT, cv::bgsegm::BackgroundSubtractorGMG, cv::bgsegm::BackgroundSubtractorGSOC, and cv::bgsegm::BackgroundSubtractorLSBP.


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