Package | Description |
---|---|
org.bytedeco.opencv.global | |
org.bytedeco.opencv.opencv_tracking |
Class and Description |
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AugmentedUnscentedKalmanFilterParams
\brief Augmented Unscented Kalman filter parameters.
|
UnscentedKalmanFilter
\brief The interface for Unscented Kalman filter and Augmented Unscented Kalman filter.
|
UnscentedKalmanFilterParams
\brief Unscented Kalman filter parameters.
|
Class and Description |
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AugmentedUnscentedKalmanFilterParams
\brief Augmented Unscented Kalman filter parameters.
|
ClfMilBoost
\addtogroup tracking
\{
|
ClfMilBoost.Params |
ClfOnlineStump |
ConfidenceMap |
ConfidenceMapVector |
ConfidenceMapVector.Iterator |
CvFeatureEvaluator |
CvFeatureParams |
CvHaarEvaluator |
CvHaarEvaluator.FeatureHaar |
CvHaarFeatureParams |
CvHOGEvaluator |
CvHOGFeatureParams |
CvLBPEvaluator |
CvLBPFeatureParams |
CvParams |
EstimatedGaussDistribution |
MultiTracker
\brief This class is used to track multiple objects using the specified tracker algorithm.
|
MultiTracker_Alt
\brief Base abstract class for the long-term Multi Object Trackers:
|
MultiTrackerTLD
\brief Multi Object %Tracker for TLD.
|
StringTrackerFeaturePairVector |
StringTrackerSamplerAlgorithmPairVector |
StrongClassifierDirectSelection
\addtogroup tracking
\{
|
Tracker
\brief Base abstract class for the long-term tracker:
|
TrackerBoosting
\brief the Boosting tracker
|
TrackerBoosting.Params |
TrackerCSRT
\brief the CSRT tracker
|
TrackerCSRT.Params |
TrackerFeature
\brief Abstract base class for TrackerFeature that represents the feature.
|
TrackerFeatureHAAR
\brief TrackerFeature based on HAAR features, used by TrackerMIL and many others algorithms
\note HAAR features implementation is copied from apps/traincascade and modified according to MIL
|
TrackerFeatureHAAR.Params |
TrackerFeatureHOG
\brief TrackerFeature based on HOG
|
TrackerFeatureLBP
\brief TrackerFeature based on LBP
|
TrackerFeatureSet
\brief Class that manages the extraction and selection of features
|
TrackerGOTURN
\brief the GOTURN (Generic Object Tracking Using Regression Networks) tracker
|
TrackerGOTURN.Params |
TrackerKCF
\brief the KCF (Kernelized Correlation Filter) tracker
|
TrackerKCF.Arg0_Mat_Rect_Mat |
TrackerKCF.Params |
TrackerMedianFlow
\brief the Median Flow tracker
|
TrackerMedianFlow.Params |
TrackerMIL
\brief The MIL algorithm trains a classifier in an online manner to separate the object from the
background.
|
TrackerMIL.Params |
TrackerMOSSE
\brief the MOSSE (Minimum Output Sum of Squared %Error) tracker
|
TrackerSampler
\brief Class that manages the sampler in order to select regions for the update the model of the tracker
|
TrackerSamplerAlgorithm
\brief Abstract base class for TrackerSamplerAlgorithm that represents the algorithm for the specific
sampler.
|
TrackerSamplerCS
\brief TrackerSampler based on CS (current state), used by algorithm TrackerBoosting
|
TrackerSamplerCS.Params |
TrackerSamplerCSC
\brief TrackerSampler based on CSC (current state centered), used by MIL algorithm TrackerMIL
|
TrackerSamplerCSC.Params |
TrackerSamplerPF.Params
\brief This structure contains all the parameters that can be varied during the course of sampling
algorithm.
|
TrackerStateEstimator
\brief Abstract base class for TrackerStateEstimator that estimates the most likely target state.
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TrackerStateEstimatorSVM
\brief TrackerStateEstimator based on SVM
|
TrackerTargetState
\brief Abstract base class for TrackerTargetState that represents a possible state of the target.
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TrackerTLD
\brief the TLD (Tracking, learning and detection) tracker
|
TrackerTLD.Params |
TrackerVector |
TrackerVector.Iterator |
Trajectory |
Trajectory.Iterator |
UkfSystemModel
\brief Model of dynamical system for Unscented Kalman filter.
|
UnscentedKalmanFilterParams
\brief Unscented Kalman filter parameters.
|
WeakClassifierHaarFeature |
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