Class cv::bgsegm::BackgroundSubtractorMOG#

Gaussian Mixture-based Background/Foreground Segmentation Algorithm. View details

#include <opencv2/bgsegm.hpp>

Collaboration diagram for cv::bgsegm::BackgroundSubtractorMOG:

cv::bgsegm::BackgroundSubtractorMOG Node1 cv::bgsegm::BackgroundSubtractorMOG   + apply() + apply() + getBackgroundRatio() + getHistory() + getNMixtures() + getNoiseSigma() + setBackgroundRatio() + setHistory() + setNMixtures() + setNoiseSigma() Node2 cv::BackgroundSubtractor   + apply() + apply() + getBackgroundImage() Node2->Node1 Node3 cv::Algorithm   + Algorithm() + ~Algorithm() + clear() + empty() + getDefaultName() + read() + save() + write() + write() + load() + loadFromString() + read() # writeFormat() Node3->Node2

cv::bgsegm::BackgroundSubtractorMOG Node1 cv::bgsegm::BackgroundSubtractorMOG   + apply() + apply() + getBackgroundRatio() + getHistory() + getNMixtures() + getNoiseSigma() + setBackgroundRatio() + setHistory() + setNMixtures() + setNoiseSigma() Node2 cv::BackgroundSubtractor   + apply() + apply() + getBackgroundImage() Node2->Node1 Node3 cv::Algorithm   + Algorithm() + ~Algorithm() + clear() + empty() + getDefaultName() + read() + save() + write() + write() + load() + loadFromString() + read() # writeFormat() Node3->Node2

Public Member Functions#

Public Member Functions inherited from cv::BackgroundSubtractor

Return

Name

Description

void

apply(
    InputArray image,
    InputArray knownForegroundMask,
    OutputArray fgmask,
    double learningRate = -1 )

Computes a foreground mask with known foreground mask input.

void

apply(
    InputArray image,
    OutputArray fgmask,
    double learningRate = -1 )

Computes a foreground mask.

void

getBackgroundImage(OutputArray backgroundImage)

Computes a background image.
Public Member Functions inherited from cv::Algorithm

Return

Name

Description

Algorithm()

~Algorithm()

void

clear()

Clears the algorithm state.

bool

empty()

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read.

String

getDefaultName()

void

read(const FileNode & fn)

Reads algorithm parameters from a file storage.

void

save(const String & filename)

void

write(
    const Ptr< FileStorage > & fs,
    const String & name = String() )

void

write(FileStorage & fs)

Stores algorithm parameters in a file storage.

void

write(
    FileStorage & fs,
    const String & name )

Static Public Member Functions#

Static Public Member Functions inherited from cv::Algorithm

Return

Name

Description

static Ptr< _Tp >

load(
    const String & filename,
    const String & objname = String() )

Loads algorithm from the file.

static Ptr< _Tp >

loadFromString(
    const String & strModel,
    const String & objname = String() )

Loads algorithm from a String.

static Ptr< _Tp >

read(const FileNode & fn)

Reads algorithm from the file node.

Additional Inherited Members#

Protected Member Functions inherited from cv::Algorithm

Return

Name

Description

void

writeFormat(FileStorage & fs)

Detailed Description#

Gaussian Mixture-based Background/Foreground Segmentation Algorithm.

The class implements the algorithm described in KB2001 .

Member Function Documentation#

apply()#

void cv::bgsegm::BackgroundSubtractorMOG::apply(
InputArray image,
InputArray knownForegroundMask,
OutputArray fgmask,
double learningRate = -1 )

Computes a foreground mask and skips known foreground in evaluation.

Parameters

  • image — Next video frame of type CV_8UC(n),CV_8SC(n),CV_16UC(n),CV_16SC(n),CV_32SC(n),CV_32FC(n),CV_64FC(n), where n is 1,2,3,4.

  • fgmask — The output foreground mask as an 8-bit binary image.

  • knownForegroundMask — The mask for inputting already known foreground, allows model to ignore learning known pixels.

  • 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.

apply()#

void cv::bgsegm::BackgroundSubtractorMOG::apply(
InputArray image,
OutputArray fgmask,
double learningRate = -1 )

Computes a foreground mask.

Parameters

  • image — Next video frame of type CV_8UC(n),CV_8SC(n),CV_16UC(n),CV_16SC(n),CV_32SC(n),CV_32FC(n),CV_64FC(n), where n is 1,2,3,4.

  • 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.

getBackgroundRatio()#

double cv::bgsegm::BackgroundSubtractorMOG::getBackgroundRatio()

getHistory()#

int cv::bgsegm::BackgroundSubtractorMOG::getHistory()

getNMixtures()#

int cv::bgsegm::BackgroundSubtractorMOG::getNMixtures()

getNoiseSigma()#

double cv::bgsegm::BackgroundSubtractorMOG::getNoiseSigma()

setBackgroundRatio()#

void cv::bgsegm::BackgroundSubtractorMOG::setBackgroundRatio(double backgroundRatio)

setHistory()#

void cv::bgsegm::BackgroundSubtractorMOG::setHistory(int nframes)

setNMixtures()#

void cv::bgsegm::BackgroundSubtractorMOG::setNMixtures(int nmix)

setNoiseSigma()#

void cv::bgsegm::BackgroundSubtractorMOG::setNoiseSigma(double noiseSigma)

Source file#

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