OpenCV  4.1.0
Open Source Computer Vision
Public Member Functions | List of all members
cv::bgsegm::BackgroundSubtractorCNT Class Referenceabstract

Background subtraction based on counting. More...

#include <opencv2/bgsegm.hpp>

Inheritance diagram for cv::bgsegm::BackgroundSubtractorCNT:
cv::BackgroundSubtractor cv::Algorithm

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.
 
virtual bool getIsParallel () const =0
 Returns if we're parallelizing the algorithm.
 
virtual int getMaxPixelStability () const =0
 Returns maximum allowed credit for a pixel in history.
 
virtual int getMinPixelStability () const =0
 Returns number of frames with same pixel color to consider stable.
 
virtual bool getUseHistory () const =0
 Returns if we're giving a pixel credit for being stable for a long time.
 
virtual void setIsParallel (bool value)=0
 Sets if we're parallelizing the algorithm.
 
virtual void setMaxPixelStability (int value)=0
 Sets the maximum allowed credit for a pixel in history.
 
virtual void setMinPixelStability (int value)=0
 Sets the number of frames with same pixel color to consider stable.
 
virtual void setUseHistory (bool value)=0
 Sets if we're giving a pixel credit for being stable for a long time.
 

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

Background subtraction based on counting.

About as fast as MOG2 on a high end system. More than twice faster than MOG2 on cheap hardware (benchmarked on Raspberry Pi3).

Algorithm by Sagi Zeevi ( https://github.com/sagi-z/BackgroundSubtractorCNT )

Member Function Documentation

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

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.

Implements cv::BackgroundSubtractor.

virtual void cv::bgsegm::BackgroundSubtractorCNT::getBackgroundImage ( OutputArray  backgroundImage) const
pure virtual
Python:
backgroundImage=cv.bgsegm_BackgroundSubtractorCNT.getBackgroundImage([, 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.

Implements cv::BackgroundSubtractor.

virtual bool cv::bgsegm::BackgroundSubtractorCNT::getIsParallel ( ) const
pure virtual
Python:
retval=cv.bgsegm_BackgroundSubtractorCNT.getIsParallel()

Returns if we're parallelizing the algorithm.

virtual int cv::bgsegm::BackgroundSubtractorCNT::getMaxPixelStability ( ) const
pure virtual
Python:
retval=cv.bgsegm_BackgroundSubtractorCNT.getMaxPixelStability()

Returns maximum allowed credit for a pixel in history.

virtual int cv::bgsegm::BackgroundSubtractorCNT::getMinPixelStability ( ) const
pure virtual
Python:
retval=cv.bgsegm_BackgroundSubtractorCNT.getMinPixelStability()

Returns number of frames with same pixel color to consider stable.

virtual bool cv::bgsegm::BackgroundSubtractorCNT::getUseHistory ( ) const
pure virtual
Python:
retval=cv.bgsegm_BackgroundSubtractorCNT.getUseHistory()

Returns if we're giving a pixel credit for being stable for a long time.

virtual void cv::bgsegm::BackgroundSubtractorCNT::setIsParallel ( bool  value)
pure virtual
Python:
None=cv.bgsegm_BackgroundSubtractorCNT.setIsParallel(value)

Sets if we're parallelizing the algorithm.

virtual void cv::bgsegm::BackgroundSubtractorCNT::setMaxPixelStability ( int  value)
pure virtual
Python:
None=cv.bgsegm_BackgroundSubtractorCNT.setMaxPixelStability(value)

Sets the maximum allowed credit for a pixel in history.

virtual void cv::bgsegm::BackgroundSubtractorCNT::setMinPixelStability ( int  value)
pure virtual
Python:
None=cv.bgsegm_BackgroundSubtractorCNT.setMinPixelStability(value)

Sets the number of frames with same pixel color to consider stable.

virtual void cv::bgsegm::BackgroundSubtractorCNT::setUseHistory ( bool  value)
pure virtual
Python:
None=cv.bgsegm_BackgroundSubtractorCNT.setUseHistory(value)

Sets if we're giving a pixel credit for being stable for a long time.


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