Package boofcv.alg.background.stationary
Class BackgroundStationaryGmm_SB<T extends ImageGray<T>>
java.lang.Object
boofcv.alg.background.BackgroundModel<T>
boofcv.alg.background.BackgroundModelStationary<T>
boofcv.alg.background.stationary.BackgroundStationaryGmm<T>
boofcv.alg.background.stationary.BackgroundStationaryGmm_SB<T>
- All Implemented Interfaces:
BackgroundAlgorithmGmm
Implementation of
BackgroundAlgorithmGmm
for ImageGray
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Field Summary
Fields inherited from class boofcv.alg.background.BackgroundModel
imageType, unknownValue
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Constructor Summary
ConstructorDescriptionBackgroundStationaryGmm_SB
(float learningPeriod, float decayCoef, int maxGaussians, ImageType<T> imageType) -
Method Summary
Methods inherited from class boofcv.alg.background.stationary.BackgroundStationaryGmm
getInitialVariance, getLearningPeriod, getMaxDistance, reset, setInitialVariance, setLearningPeriod, setMaxDistance, setSignificantWeight, updateBackground
Methods inherited from class boofcv.alg.background.BackgroundModel
getImageType, getUnknownValue, setUnknownValue
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Constructor Details
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BackgroundStationaryGmm_SB
public BackgroundStationaryGmm_SB(float learningPeriod, float decayCoef, int maxGaussians, ImageType<T> imageType) - Parameters:
learningPeriod
- Specifies how fast it will adjust to changes in the image. Must be greater than zero.decayCoef
- Determines how quickly a Gaussian is forgottenmaxGaussians
- Maximum number of Gaussians in a mixture for a pixelimageType
- Type of image it's processing.
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Method Details
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updateBackground
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 classBackgroundStationaryGmm<T extends ImageGray<T>>
mask
- If null then the background mask is ignored
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segment
Description copied from class:BackgroundModelStationary
Invoke to segment input image into background and foreground pixels. If 'segmented' isn't the correct size it will be resized.- Specified by:
segment
in classBackgroundModelStationary<T extends ImageGray<T>>
- Parameters:
frame
- (input) current imagesegmented
- (output) Segmented image. 0 = background, 1 = foreground/moving
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