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java.lang.Objectde.unihalle.informatik.MiToBo.math.distributions.impl.ParticleDistribution<RBMCDASample<T>>
de.unihalle.informatik.MiToBo.tracking.multitarget.algo.MultiTargetRBMCDA<T>
T
- @ALDMetaInfo(export=ALLOWED) public class MultiTargetRBMCDA<T extends TargetID>
Rao-Blackwellized Monte Carlo Data Association following:
S. Saerkkae, A. Vehtari and J. Lampinen, "Rao-Blackwellized particle filter for multiple target tracking",
Information Fusion, Vol 8, No 1, 2007, pages 2-15
Monte Carlo sampling in the space of association variables while state distributions are kept in closed form.
Association variables determine association of observations to targets.
Field Summary | |
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protected AssociationDistribution<T,T> |
assocDistrib
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protected double |
esspercentage
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protected Vector<HashMap<Integer,Integer>> |
groundtruthToSampleTargetIDs
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OutputStream |
ostream
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Fields inherited from class de.unihalle.informatik.MiToBo.math.distributions.impl.ParticleDistribution |
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cweights, equalWeights, particles, rand, weights |
Constructor Summary | |
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MultiTargetRBMCDA(Random rand,
RBMCDASample<T>[] initialStateParticles,
AssociationDistribution<T,T> assocDistrib)
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MultiTargetRBMCDA(Random rand,
RBMCDASample<T> initialState,
int numParticles,
AssociationDistribution<T,T> assocDistrib)
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Method Summary | |
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MultiTargetPredictionFilter<AbstractMultiState<T>> |
copy()
Not implemented, always returns null |
double |
getESSPercentage()
If this percentage of number of samples is below the current effective sample size (ESS), the samples are resampled. |
AbstractMultiState<T> |
getMean()
|
void |
predict()
Prediction step method |
void |
setESSPercentage(double essPercentage)
Set percentage of number of samples used to determine if resampling is required, i.e. if it is below the current effective sample size (ESS). |
void |
update(AbstractMultiState<T> observation,
DataAssociation association)
The DataAssociation object may be null and is interpreted as groundtruth if given. |
Methods inherited from class de.unihalle.informatik.MiToBo.math.distributions.impl.ParticleDistribution |
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computeESS, drawSample, equalWeights, getNumOfParticles, getParticle, getParticles, getWeight, getWeights, normalizeWeights, resample, setEqualWeightsFlag, setParticle, setWeight |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Field Detail |
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protected AssociationDistribution<T extends TargetID,T extends TargetID> assocDistrib
protected double esspercentage
public OutputStream ostream
protected Vector<HashMap<Integer,Integer>> groundtruthToSampleTargetIDs
Constructor Detail |
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public MultiTargetRBMCDA(Random rand, RBMCDASample<T> initialState, int numParticles, AssociationDistribution<T,T> assocDistrib)
public MultiTargetRBMCDA(Random rand, RBMCDASample<T>[] initialStateParticles, AssociationDistribution<T,T> assocDistrib)
Method Detail |
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public AbstractMultiState<T> getMean()
getMean
in interface FirstOrderMoment<AbstractMultiState<T extends TargetID>>
public MultiTargetPredictionFilter<AbstractMultiState<T>> copy()
null
copy
in interface Copyable<MultiTargetPredictionFilter<AbstractMultiState<T extends TargetID>>>
public void predict()
MultiTargetPredictionFilter
predict
in interface MultiTargetPredictionFilter<AbstractMultiState<T extends TargetID>>
public void update(AbstractMultiState<T> observation, DataAssociation association)
update
in interface MultiTargetPredictionFilter<AbstractMultiState<T extends TargetID>>
public double getESSPercentage()
public void setESSPercentage(double essPercentage)
essPercentage
- percentage in range [0,1] of the number of samples. 0=no resampling ... 1=resamping in every time step.
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