OpenCV  3.3.0-dev
Open Source Computer Vision
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cv::cuda::BackgroundSubtractorMOG Class Referenceabstract

Gaussian Mixture-based Background/Foreground Segmentation Algorithm. More...

#include "cudabgsegm.hpp"

Inheritance diagram for cv::cuda::BackgroundSubtractorMOG:
cv::BackgroundSubtractor cv::Algorithm

Public Member Functions

virtual void apply (InputArray image, OutputArray fgmask, double learningRate, Stream &stream)=0
 
virtual void getBackgroundImage (OutputArray backgroundImage, Stream &stream) const =0
 
virtual double getBackgroundRatio () const =0
 
virtual int getHistory () const =0
 
virtual int getNMixtures () const =0
 
virtual double getNoiseSigma () const =0
 
virtual void setBackgroundRatio (double backgroundRatio)=0
 
virtual void setHistory (int nframes)=0
 
virtual void setNMixtures (int nmix)=0
 
virtual void setNoiseSigma (double noiseSigma)=0
 
- Public Member Functions inherited from cv::BackgroundSubtractor
virtual void apply (InputArray image, OutputArray fgmask, double learningRate=-1)=0
 Computes a foreground mask. More...
 
virtual void getBackgroundImage (OutputArray backgroundImage) const =0
 Computes a background image. More...
 
- Public Member Functions inherited from cv::Algorithm
 Algorithm ()
 
virtual ~Algorithm ()
 
virtual void clear ()
 Clears the algorithm state. More...
 
virtual bool empty () const
 Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read. More...
 
virtual String getDefaultName () const
 
virtual void read (const FileNode &fn)
 Reads algorithm parameters from a file storage. More...
 
virtual void save (const String &filename) const
 
virtual void write (FileStorage &fs) const
 Stores algorithm parameters in a file storage. More...
 

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. More...
 
template<typename _Tp >
static Ptr< _Tp > loadFromString (const String &strModel, const String &objname=String())
 Loads algorithm from a String. More...
 
template<typename _Tp >
static Ptr< _Tp > read (const FileNode &fn)
 Reads algorithm from the file node. More...
 
- Protected Member Functions inherited from cv::Algorithm
void writeFormat (FileStorage &fs) const
 

Detailed Description

Gaussian Mixture-based Background/Foreground Segmentation Algorithm.

The class discriminates between foreground and background pixels by building and maintaining a model of the background. Any pixel which does not fit this model is then deemed to be foreground. The class implements algorithm described in [MOG2001] .

See also
BackgroundSubtractorMOG
Note
  • An example on gaussian mixture based background/foreground segmantation can be found at opencv_source_code/samples/gpu/bgfg_segm.cpp

Member Function Documentation

◆ apply()

virtual void cv::cuda::BackgroundSubtractorMOG::apply ( InputArray  image,
OutputArray  fgmask,
double  learningRate,
Stream stream 
)
pure virtual

◆ getBackgroundImage()

virtual void cv::cuda::BackgroundSubtractorMOG::getBackgroundImage ( OutputArray  backgroundImage,
Stream stream 
) const
pure virtual

◆ getBackgroundRatio()

virtual double cv::cuda::BackgroundSubtractorMOG::getBackgroundRatio ( ) const
pure virtual

◆ getHistory()

virtual int cv::cuda::BackgroundSubtractorMOG::getHistory ( ) const
pure virtual

◆ getNMixtures()

virtual int cv::cuda::BackgroundSubtractorMOG::getNMixtures ( ) const
pure virtual

◆ getNoiseSigma()

virtual double cv::cuda::BackgroundSubtractorMOG::getNoiseSigma ( ) const
pure virtual

◆ setBackgroundRatio()

virtual void cv::cuda::BackgroundSubtractorMOG::setBackgroundRatio ( double  backgroundRatio)
pure virtual

◆ setHistory()

virtual void cv::cuda::BackgroundSubtractorMOG::setHistory ( int  nframes)
pure virtual

◆ setNMixtures()

virtual void cv::cuda::BackgroundSubtractorMOG::setNMixtures ( int  nmix)
pure virtual

◆ setNoiseSigma()

virtual void cv::cuda::BackgroundSubtractorMOG::setNoiseSigma ( double  noiseSigma)
pure virtual

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