Class cv::bgsegm::BackgroundSubtractorGMG#

Background Subtractor module based on the algorithm given in [119] . View details

#include <opencv2/bgsegm.hpp>

Collaboration diagram for cv::bgsegm::BackgroundSubtractorGMG:

cv::bgsegm::BackgroundSubtractorGMG Node1 cv::bgsegm::BackgroundSubtractorGMG   + apply() + apply() + getBackgroundImage() + getBackgroundPrior() + getDecisionThreshold() + getDefaultLearningRate() + getMaxFeatures() + getMaxVal() + getMinVal() + getNumFrames() and 13 more... 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::BackgroundSubtractorGMG Node1 cv::bgsegm::BackgroundSubtractorGMG   + apply() + apply() + getBackgroundImage() + getBackgroundPrior() + getDecisionThreshold() + getDefaultLearningRate() + getMaxFeatures() + getMaxVal() + getMinVal() + getNumFrames() and 13 more... 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#

Background Subtractor module based on the algorithm given in Gold2012 .

Takes a series of images and returns a sequence of mask (8UC1) images of the same size, where 255 indicates Foreground and 0 represents Background. This class implements an algorithm described in “Visual Tracking of Human Visitors under

Variable-Lighting Conditions for a Responsive Audio Art Installation,” A. Godbehere, A. Matsukawa, K. Goldberg, American Control Conference, Montreal, June 2012.

Member Function Documentation#

apply()#

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

Computes a foreground mask with known foreground mask input.

Note

This method has a default virtual implementation that throws a “not implemented” error. Foreground masking may not be supported by all background subtractors.

Parameters

  • image — Next video frame.

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

  • knownForegroundMask — The mask for inputting already known foreground.

  • 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::BackgroundSubtractorGMG::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.

getBackgroundImage()#

void cv::bgsegm::BackgroundSubtractorGMG::getBackgroundImage(OutputArray backgroundImage)

Computes a background image.

Note

Sometimes the background image can be very blurry, as it contain the average background statistics.

Parameters

  • backgroundImage — The output background image.

getBackgroundPrior()#

double cv::bgsegm::BackgroundSubtractorGMG::getBackgroundPrior()

Returns the prior probability that each individual pixel is a background pixel.

getDecisionThreshold()#

double cv::bgsegm::BackgroundSubtractorGMG::getDecisionThreshold()

Returns the value of decision threshold.

Decision value is the value above which pixel is determined to be FG.

getDefaultLearningRate()#

double cv::bgsegm::BackgroundSubtractorGMG::getDefaultLearningRate()

Returns the learning rate of the algorithm.

It lies between 0.0 and 1.0. It determines how quickly features are “forgotten” from histograms.

getMaxFeatures()#

int cv::bgsegm::BackgroundSubtractorGMG::getMaxFeatures()

Returns total number of distinct colors to maintain in histogram.

getMaxVal()#

double cv::bgsegm::BackgroundSubtractorGMG::getMaxVal()

Returns the maximum value taken on by pixels in image sequence. e.g. 1.0 or 255.

getMinVal()#

double cv::bgsegm::BackgroundSubtractorGMG::getMinVal()

Returns the minimum value taken on by pixels in image sequence. Usually 0.

getNumFrames()#

int cv::bgsegm::BackgroundSubtractorGMG::getNumFrames()

Returns the number of frames used to initialize background model.

getQuantizationLevels()#

int cv::bgsegm::BackgroundSubtractorGMG::getQuantizationLevels()

Returns the parameter used for quantization of color-space.

It is the number of discrete levels in each channel to be used in histograms.

getSmoothingRadius()#

int cv::bgsegm::BackgroundSubtractorGMG::getSmoothingRadius()

Returns the kernel radius used for morphological operations.

getUpdateBackgroundModel()#

bool cv::bgsegm::BackgroundSubtractorGMG::getUpdateBackgroundModel()

Returns the status of background model update.

setBackgroundPrior()#

void cv::bgsegm::BackgroundSubtractorGMG::setBackgroundPrior(double bgprior)

Sets the prior probability that each individual pixel is a background pixel.

setDecisionThreshold()#

void cv::bgsegm::BackgroundSubtractorGMG::setDecisionThreshold(double thresh)

Sets the value of decision threshold.

setDefaultLearningRate()#

void cv::bgsegm::BackgroundSubtractorGMG::setDefaultLearningRate(double lr)

Sets the learning rate of the algorithm.

setMaxFeatures()#

void cv::bgsegm::BackgroundSubtractorGMG::setMaxFeatures(int maxFeatures)

Sets total number of distinct colors to maintain in histogram.

setMaxVal()#

void cv::bgsegm::BackgroundSubtractorGMG::setMaxVal(double val)

Sets the maximum value taken on by pixels in image sequence.

setMinVal()#

void cv::bgsegm::BackgroundSubtractorGMG::setMinVal(double val)

Sets the minimum value taken on by pixels in image sequence.

setNumFrames()#

void cv::bgsegm::BackgroundSubtractorGMG::setNumFrames(int nframes)

Sets the number of frames used to initialize background model.

setQuantizationLevels()#

void cv::bgsegm::BackgroundSubtractorGMG::setQuantizationLevels(int nlevels)

Sets the parameter used for quantization of color-space.

setSmoothingRadius()#

void cv::bgsegm::BackgroundSubtractorGMG::setSmoothingRadius(int radius)

Sets the kernel radius used for morphological operations.

setUpdateBackgroundModel()#

void cv::bgsegm::BackgroundSubtractorGMG::setUpdateBackgroundModel(bool update)

Sets the status of background model update.

Source file#

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