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

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>

Inheritance diagram for cv::bgsegm::BackgroundSubtractorGSOC:
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.
 

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

virtual void cv::bgsegm::BackgroundSubtractorGSOC::apply ( InputArray  image,
OutputArray  fgmask,
double  learningRate = -1 
)
pure virtual
Python:
fgmask=cv.bgsegm_BackgroundSubtractorGSOC.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::BackgroundSubtractorGSOC::getBackgroundImage ( OutputArray  backgroundImage) const
pure virtual
Python:
backgroundImage=cv.bgsegm_BackgroundSubtractorGSOC.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.


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