Package boofcv.alg.background.stationary

Class BackgroundStationaryGmm<T extends ImageBase<T>>

java.lang.Object

boofcv.alg.background.BackgroundModel<T>

boofcv.alg.background.BackgroundModelStationary<T>

boofcv.alg.background.stationary.BackgroundStationaryGmm<T>

All Implemented Interfaces:

BackgroundAlgorithmGmm

Direct Known Subclasses:

BackgroundStationaryGmm_MB, BackgroundStationaryGmm_MB_MT, BackgroundStationaryGmm_SB, BackgroundStationaryGmm_SB_MT

public abstract class BackgroundStationaryGmm<T extends ImageBase<T>>
extends BackgroundModelStationary<T>
implements BackgroundAlgorithmGmm

Implementation of BackgroundAlgorithmGmm for stationary images.

See Also:

• BackgroundModelStationary

Field Summary

Fields inherited from class boofcv.alg.background.BackgroundModel

imageType, unknownValue

Constructor Summary

Constructors

Modifier	Constructor	Description
protected	BackgroundStationaryGmm(float learningPeriod, float decayCoef, int maxGaussians, ImageType<T> imageType)

Method Summary

Modifier and Type	Method	Description
float	getInitialVariance()	Returns the initial variance assigned to a pixel
float	getLearningPeriod()	Returns the learning period.
float	getMaxDistance()
void	reset()	Resets model to its original state
void	setInitialVariance(float initialVariance)	Sets the initial variance assigned to a pixel
void	setLearningPeriod(float period)	Specifies the learning rate
void	setMaxDistance(float maxDistance)
void	setSignificantWeight(float value)	Minimum value of a Gaussian's weight to be considered part of the background
void	updateBackground(T frame)	Updates the background with new image information.
void	updateBackground(T frame, @Nullable GrayU8 mask)	Updates the background and segments it at the same time.

Methods inherited from class boofcv.alg.background.BackgroundModelStationary

segment

Methods inherited from class boofcv.alg.background.BackgroundModel

getImageType, getUnknownValue, setUnknownValue

Methods inherited from class java.lang.Object

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

Constructor Details

BackgroundStationaryGmm

protected BackgroundStationaryGmm(float learningPeriod,
 float decayCoef,
 int maxGaussians,
 ImageType<T> imageType)

Method Details

reset

public void reset()

Description copied from class: BackgroundModel

Resets model to its original state

Specified by:

reset in class BackgroundModel<T extends ImageBase<T>>

updateBackground

public void updateBackground(T frame)

Description copied from class: BackgroundModelStationary

Updates the background with new image information.

Specified by:

updateBackground in class BackgroundModelStationary<T extends ImageBase<T>>

updateBackground

public void updateBackground(T frame,
 @Nullable
 @Nullable GrayU8 mask)

Description copied from class: BackgroundModelStationary

Updates the background and segments it at the same time. In some implementations this can be significantly faster than doing it with separate function calls. Segmentation is performed using the model which it has prior to the update.

Overrides:

updateBackground in class BackgroundModelStationary<T extends ImageBase<T>>

Parameters:

mask - If null then the background mask is ignored

getInitialVariance

public float getInitialVariance()

Description copied from interface: BackgroundAlgorithmGmm

Returns the initial variance assigned to a pixel

Specified by:

getInitialVariance in interface BackgroundAlgorithmGmm

Returns:

initial variance

setInitialVariance

public void setInitialVariance(float initialVariance)

Description copied from interface: BackgroundAlgorithmGmm

Sets the initial variance assigned to a pixel

Specified by:

setInitialVariance in interface BackgroundAlgorithmGmm

Parameters:

initialVariance - initial variance

getLearningPeriod

public float getLearningPeriod()

Description copied from interface: BackgroundAlgorithmGmm

Returns the learning period.

Specified by:

getLearningPeriod in interface BackgroundAlgorithmGmm

setLearningPeriod

public void setLearningPeriod(float period)

Description copied from interface: BackgroundAlgorithmGmm

Specifies the learning rate

Specified by:

setLearningPeriod in interface BackgroundAlgorithmGmm

Parameters:

period - Must be more than 0.

setSignificantWeight

public void setSignificantWeight(float value)

Description copied from interface: BackgroundAlgorithmGmm

Minimum value of a Gaussian's weight to be considered part of the background

Specified by:

setSignificantWeight in interface BackgroundAlgorithmGmm

getMaxDistance

public float getMaxDistance()

setMaxDistance

public void setMaxDistance(float maxDistance)