Package boofcv.alg.background.stationary

Class BackgroundStationaryGaussian<T extends ImageBase<T>>

java.lang.Object

boofcv.alg.background.BackgroundModel<T>

boofcv.alg.background.BackgroundModelStationary<T>

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

All Implemented Interfaces:

BackgroundAlgorithmGaussian

Direct Known Subclasses:

BackgroundStationaryGaussian_IL, BackgroundStationaryGaussian_IL_MT, BackgroundStationaryGaussian_PL, BackgroundStationaryGaussian_PL_MT, BackgroundStationaryGaussian_SB, BackgroundStationaryGaussian_SB_MT

public abstract class BackgroundStationaryGaussian<T extends ImageBase<T>>
extends BackgroundModelStationary<T>
implements BackgroundAlgorithmGaussian

Implementation of BackgroundAlgorithmGaussian for stationary images.

See Also:

• BackgroundAlgorithmGaussian
• BackgroundModelStationary

Field Summary

Fields

Modifier and Type	Field	Description
protected float	initialVariance	The initial variance assigned to a new pixel.
protected float	learnRate	Specifies how fast it will adapt.
protected float	minimumDifference
protected float	threshold	Threshold for classifying a pixel as background or not.

Fields inherited from class boofcv.alg.background.BackgroundModel

imageType, unknownValue

Constructor Summary

Constructors

Modifier	Constructor	Description
protected	BackgroundStationaryGaussian(float learnRate, float threshold, ImageType<T> imageType)	See class documentation for parameters definitions.

Method Summary

Methods inherited from class boofcv.alg.background.BackgroundModelStationary

segment, updateBackground, updateBackground

Methods inherited from class boofcv.alg.background.BackgroundModel

getImageType, getUnknownValue, reset, setUnknownValue

Methods inherited from class java.lang.Object

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

Methods inherited from interface boofcv.alg.background.BackgroundAlgorithmGaussian

getInitialVariance, getLearnRate, getMinimumDifference, getThreshold, setInitialVariance, setLearnRate, setMinimumDifference, setThreshold

Field Details

learnRate

protected float learnRate

Specifies how fast it will adapt. 0 to 1, inclusive. 0 = static 1.0 = instant.

threshold

protected float threshold

Threshold for classifying a pixel as background or not. This threshold is applied to the computed Mahalanobis from the distribution.

initialVariance

protected float initialVariance

The initial variance assigned to a new pixel. Larger values to reduce false positives due to under sampling

minimumDifference

protected float minimumDifference

Constructor Details

BackgroundStationaryGaussian

protected BackgroundStationaryGaussian(float learnRate,
 float threshold,
 ImageType<T> imageType)

See class documentation for parameters definitions.

Parameters:

learnRate - Specifies how quickly the background is updated Try 0.05

threshold - Threshold for background. ≥ 0. Try 10

imageType - Type of input image