Package org.opencv.bgsegm

Class BackgroundSubtractorMOG

java.lang.Object

org.opencv.core.Algorithm

org.opencv.video.BackgroundSubtractor

org.opencv.bgsegm.BackgroundSubtractorMOG

public class BackgroundSubtractorMOG
extends BackgroundSubtractor

Gaussian Mixture-based Background/Foreground Segmentation Algorithm. The class implements the algorithm described in CITE: KB2001 .

Field Summary

Fields inherited from class org.opencv.core.Algorithm

nativeObj

Constructor Summary

Constructors

Modifier	Constructor	Description
protected	BackgroundSubtractorMOG(long addr)

Method Summary

Modifier and Type	Method	Description
static BackgroundSubtractorMOG	__fromPtr__(long addr)
void	apply(Mat image, Mat fgmask)	Computes a foreground mask.
void	apply(Mat image, Mat fgmask, double learningRate)	Computes a foreground mask.
void	apply(Mat image, Mat knownForegroundMask, Mat fgmask)	Computes a foreground mask and skips known foreground in evaluation.
void	apply(Mat image, Mat knownForegroundMask, Mat fgmask, double learningRate)	Computes a foreground mask and skips known foreground in evaluation.
protected void	finalize()
double	getBackgroundRatio()
int	getHistory()
int	getNMixtures()
double	getNoiseSigma()
void	setBackgroundRatio(double backgroundRatio)
void	setHistory(int nframes)
void	setNMixtures(int nmix)
void	setNoiseSigma(double noiseSigma)

Methods inherited from class org.opencv.video.BackgroundSubtractor

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

BackgroundSubtractorMOG

protected BackgroundSubtractorMOG(long addr)

Method Detail

__fromPtr__

public static BackgroundSubtractorMOG __fromPtr__(long addr)

apply

public void apply(Mat image,
                  Mat fgmask,
                  double learningRate)

Computes a foreground mask.

Overrides:

apply in class BackgroundSubtractor

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.

apply

public void apply(Mat image,
                  Mat fgmask)

Computes a foreground mask.

Overrides:

apply in class BackgroundSubtractor

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. 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

public void apply(Mat image,
                  Mat knownForegroundMask,
                  Mat fgmask,
                  double learningRate)

Computes a foreground mask and skips known foreground in evaluation.

Overrides:

apply in class BackgroundSubtractor

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

public void apply(Mat image,
                  Mat knownForegroundMask,
                  Mat fgmask)

Computes a foreground mask and skips known foreground in evaluation.

Overrides:

apply in class BackgroundSubtractor

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. 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.

getHistory

public int getHistory()

setHistory

public void setHistory(int nframes)

getNMixtures

public int getNMixtures()

setNMixtures

public void setNMixtures(int nmix)

getBackgroundRatio

public double getBackgroundRatio()

setBackgroundRatio

public void setBackgroundRatio(double backgroundRatio)

getNoiseSigma

public double getNoiseSigma()

setNoiseSigma

public void setNoiseSigma(double noiseSigma)

finalize

protected void finalize()
                 throws java.lang.Throwable

Overrides:

finalize in class BackgroundSubtractor

Throws:

java.lang.Throwable