org.opencv.bgsegm

Class BackgroundSubtractorGMG

java.lang.Object

org.opencv.core.Algorithm

org.opencv.video.BackgroundSubtractor

org.opencv.bgsegm.BackgroundSubtractorGMG

public class BackgroundSubtractorGMG
extends BackgroundSubtractor

Background Subtractor module based on the algorithm given in CITE: 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.

Field Summary

Fields inherited from class org.opencv.core.Algorithm

nativeObj

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	BackgroundSubtractorGMG(long addr)

Method Summary

Modifier and Type	Method and Description
static BackgroundSubtractorGMG	__fromPtr__(long addr)
protected void	finalize()
double	getBackgroundPrior() Returns the prior probability that each individual pixel is a background pixel.
double	getDecisionThreshold() Returns the value of decision threshold.
double	getDefaultLearningRate() Returns the learning rate of the algorithm.
int	getMaxFeatures() Returns total number of distinct colors to maintain in histogram.
double	getMaxVal() Returns the maximum value taken on by pixels in image sequence.
double	getMinVal() Returns the minimum value taken on by pixels in image sequence.
int	getNumFrames() Returns the number of frames used to initialize background model.
int	getQuantizationLevels() Returns the parameter used for quantization of color-space.
int	getSmoothingRadius() Returns the kernel radius used for morphological operations
boolean	getUpdateBackgroundModel() Returns the status of background model update
void	setBackgroundPrior(double bgprior) Sets the prior probability that each individual pixel is a background pixel.
void	setDecisionThreshold(double thresh) Sets the value of decision threshold.
void	setDefaultLearningRate(double lr) Sets the learning rate of the algorithm.
void	setMaxFeatures(int maxFeatures) Sets total number of distinct colors to maintain in histogram.
void	setMaxVal(double val) Sets the maximum value taken on by pixels in image sequence.
void	setMinVal(double val) Sets the minimum value taken on by pixels in image sequence.
void	setNumFrames(int nframes) Sets the number of frames used to initialize background model.
void	setQuantizationLevels(int nlevels) Sets the parameter used for quantization of color-space
void	setSmoothingRadius(int radius) Sets the kernel radius used for morphological operations
void	setUpdateBackgroundModel(boolean update) Sets the status of background model update

Methods inherited from class org.opencv.video.BackgroundSubtractor

apply, apply, getBackgroundImage

Methods inherited from class org.opencv.core.Algorithm

clear, empty, getDefaultName, getNativeObjAddr, save

Methods inherited from class java.lang.Object

clone, equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

BackgroundSubtractorGMG

protected BackgroundSubtractorGMG(long addr)

Method Detail

__fromPtr__

public static BackgroundSubtractorGMG __fromPtr__(long addr)

getUpdateBackgroundModel

public boolean getUpdateBackgroundModel()

Returns the status of background model update

Returns:

automatically generated

getBackgroundPrior

public double getBackgroundPrior()

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

Returns:

automatically generated

getDecisionThreshold

public double getDecisionThreshold()

Returns the value of decision threshold. Decision value is the value above which pixel is determined to be FG.

Returns:

automatically generated

getDefaultLearningRate

public double 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.

Returns:

automatically generated

getMaxVal

public double getMaxVal()

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

Returns:

automatically generated

getMinVal

public double getMinVal()

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

Returns:

automatically generated

getMaxFeatures

public int getMaxFeatures()

Returns total number of distinct colors to maintain in histogram.

Returns:

automatically generated

getNumFrames

public int getNumFrames()

Returns the number of frames used to initialize background model.

Returns:

automatically generated

getQuantizationLevels

public int 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.

Returns:

automatically generated

getSmoothingRadius

public int getSmoothingRadius()

Returns the kernel radius used for morphological operations

Returns:

automatically generated

setBackgroundPrior

public void setBackgroundPrior(double bgprior)

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

Parameters:

bgprior - automatically generated

setDecisionThreshold

public void setDecisionThreshold(double thresh)

Sets the value of decision threshold.

Parameters:

thresh - automatically generated

setDefaultLearningRate

public void setDefaultLearningRate(double lr)

Sets the learning rate of the algorithm.

Parameters:

lr - automatically generated

setMaxFeatures

public void setMaxFeatures(int maxFeatures)

Sets total number of distinct colors to maintain in histogram.

Parameters:

maxFeatures - automatically generated

setMaxVal

public void setMaxVal(double val)

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

Parameters:

val - automatically generated

setMinVal

public void setMinVal(double val)

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

Parameters:

val - automatically generated

setNumFrames

public void setNumFrames(int nframes)

Sets the number of frames used to initialize background model.

Parameters:

nframes - automatically generated

setQuantizationLevels

public void setQuantizationLevels(int nlevels)

Sets the parameter used for quantization of color-space

Parameters:

nlevels - automatically generated

setSmoothingRadius

public void setSmoothingRadius(int radius)

Sets the kernel radius used for morphological operations

Parameters:

radius - automatically generated

setUpdateBackgroundModel

public void setUpdateBackgroundModel(boolean update)

Sets the status of background model update

Parameters:

update - automatically generated

finalize

protected void finalize()
                 throws Throwable

Overrides:

finalize in class BackgroundSubtractor

Throws:

Throwable