boofcv.alg.tracker.tld

Class TldFernClassifier<T extends ImageGray>

java.lang.Object

boofcv.alg.tracker.tld.TldFernClassifier<T>

public class TldFernClassifier<T extends ImageGray>
extends java.lang.Object

Manages ferns, creates their descriptions, compute their values, and handles their probabilities.

Constructor Summary

Constructors

Constructor and Description
TldFernClassifier(java.util.Random rand, int numFerns, int descriptorSize, int numLearnRandom, float fernLearnNoise, InterpolatePixelS<T> interpolate) Configures fern algorithm

Method Summary

Modifier and Type	Method and Description
int	getMaxN()
int	getMaxP()
void	learnFern(boolean positive, ImageRectangle r) Learns a fern from the specified region.
void	learnFernNoise(boolean positive, ImageRectangle r) Computes the value for each fern inside the region and update's their P and N value.
boolean	lookupFernPN(TldRegionFernInfo info) For the specified regions, computes the values of each fern inside of it and then retrives their P and N values.
void	renormalizeN() Renormalizes fern.numN to avoid overflow
void	renormalizeP() Renormalizes fern.numP to avoid overflow
void	reset() Discard all information on fern values and their probabilities
void	setImage(T gray) Call before any other functions.

Methods inherited from class java.lang.Object

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

Constructor Detail

TldFernClassifier

public TldFernClassifier(java.util.Random rand,
                         int numFerns,
                         int descriptorSize,
                         int numLearnRandom,
                         float fernLearnNoise,
                         InterpolatePixelS<T> interpolate)

Configures fern algorithm

Parameters:

rand - Random number generated used for creating ferns

numFerns - Number of ferns to created. Typically 10

descriptorSize - Size of each fern's descriptor. Typically 10

numLearnRandom - Number of ferns which will be generated by adding noise to the image

fernLearnNoise - The noise's standard deviation

interpolate - Interpolation function for the image

Method Detail

reset

public void reset()

Discard all information on fern values and their probabilities

setImage

public void setImage(T gray)

Call before any other functions. Provides the image that is being sampled.

Parameters:

gray - Input image.

learnFern

public void learnFern(boolean positive,
                      ImageRectangle r)

Learns a fern from the specified region. No noise is added.

learnFernNoise

public void learnFernNoise(boolean positive,
                           ImageRectangle r)

Computes the value for each fern inside the region and update's their P and N value. Noise is added to the image measurements to take in account the variability.

lookupFernPN

public boolean lookupFernPN(TldRegionFernInfo info)

For the specified regions, computes the values of each fern inside of it and then retrives their P and N values. The sum of which is stored inside of info.

Parameters:

info - (Input) Location/Rectangle (output) P and N values

Returns:

true if a known value for any of the ferns was observed in this region

renormalizeP

public void renormalizeP()

Renormalizes fern.numP to avoid overflow

renormalizeN

public void renormalizeN()

Renormalizes fern.numN to avoid overflow

getMaxP

public int getMaxP()

getMaxN

public int getMaxN()