| OpenCV 5.0.0alpha Open Source Computer Vision

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Namespaces | Classes | Typedefs | Functions
cv::detail::tracking Namespace Reference

## Namespaces
namespace | contrib_feature
namespace | kalman_filters
namespace | online_boosting
namespace | tbm
namespace | tld

## Classes
class | AugmentedUnscentedKalmanFilterParams
| Augmented Unscented Kalman filter parameters. The class for initialization parameters of Augmented Unscented Kalman filter. More...
class | BaseClassifier
class | ClassifierThreshold
class | CvFeatureEvaluator
class | CvFeatureParams
class | CvHaarEvaluator
class | CvHaarFeatureParams
class | CvHOGEvaluator
struct | CvHOGFeatureParams
class | CvLBPEvaluator
struct | CvLBPFeatureParams
class | CvParams
class | Detector
class | EstimatedGaussDistribution
class | StrongClassifierDirectSelection
class | TrackerContribFeature
| Abstract base class for TrackerContribFeature that represents the feature. More...
class | TrackerContribFeatureHAAR
| TrackerContribFeature based on HAAR features, used by TrackerMIL and many others algorithms. More...
class | TrackerContribFeatureSet
| Class that manages the extraction and selection of features. More...
class | TrackerContribSampler
| Class that manages the sampler in order to select regions for the update the model of the tracker [AAM] Sampling e Labeling. See table I and section III B. More...
class | TrackerContribSamplerAlgorithm
| Abstract base class for TrackerContribSamplerAlgorithm that represents the algorithm for the specific sampler. More...
class | TrackerContribSamplerCSC
| TrackerSampler based on CSC (current state centered), used by MIL algorithm TrackerMIL. More...
class | TrackerFeature
| Abstract base class for TrackerFeature that represents the feature. More...
class | TrackerFeatureFeature2d
| TrackerContribFeature based on Feature2D. More...
class | TrackerFeatureHOG
| TrackerContribFeature based on HOG. More...
class | TrackerFeatureLBP
| TrackerContribFeature based on LBP. More...
class | TrackerFeatureSet
| Class that manages the extraction and selection of features. More...
class | TrackerModel
| Abstract class that represents the model of the target. More...
class | TrackerSampler
| Class that manages the sampler in order to select regions for the update the model of the tracker [AAM] Sampling e Labeling. See table I and section III B. More...
class | TrackerSamplerAlgorithm
| Abstract base class for TrackerSamplerAlgorithm that represents the algorithm for the specific sampler. More...
class | TrackerSamplerCS
| TrackerContribSampler based on CS (current state), used by algorithm TrackerBoosting. More...
class | TrackerSamplerCSC
| TrackerSampler based on CSC (current state centered), used by MIL algorithm TrackerMIL. More...
class | TrackerSamplerPF
| This sampler is based on particle filtering. More...
class | TrackerStateEstimator
| Abstract base class for TrackerStateEstimator that estimates the most likely target state. More...
class | TrackerStateEstimatorAdaBoosting
| TrackerStateEstimatorAdaBoosting based on ADA-Boosting. More...
class | TrackerStateEstimatorSVM
| TrackerStateEstimator based on SVM. More...
class | TrackerTargetState
| Abstract base class for TrackerTargetState that represents a possible state of the target. More...
class | UkfSystemModel
| Model of dynamical system for Unscented Kalman filter. The interface for dynamical system model. It contains functions for computing the next state and the measurement. It must be inherited for using UKF. More...
class | UnscentedKalmanFilter
| The interface for Unscented Kalman filter and Augmented Unscented Kalman filter. More...
class | UnscentedKalmanFilterParams
| Unscented Kalman filter parameters. The class for initialization parameters of Unscented Kalman filter. More...
class | WeakClassifierHaarFeature

## Typedefs
typedef std::vector< std::pair< Ptr< TrackerTargetState >, float > > | ConfidenceMap
| Represents the model of the target at frame \(k\) (all states and scores)
typedef std::vector< Ptr< TrackerTargetState > > | Trajectory
| Represents the estimate states for all frames.

## Functions
template<class Feature >
void | _writeFeatures (const std::vector< Feature > features, FileStorage &fs, const Mat &featureMap)
float | calcNormFactor (const Mat &sum, const Mat &sqSum)
void | computeInteractionMatrix (const cv::Mat &uv, const cv::Mat &depths, const cv::Mat &K, cv::Mat &J)
| Compute the interaction matrix ( [132] [52] [53] ) for a set of 2D pixels. This is usually used in visual servoing applications to command a robot to move at desired pixel locations/velocities. By inverting this matrix, one can estimate camera spatial velocity i.e., the twist.
cv::Vec6d | computeTwist (const cv::Mat &uv, const cv::Mat &duv, const cv::Mat &depths, const cv::Mat &K)
| Compute the camera twist from a set of 2D pixel locations, their velocities, depth values and intrinsic parameters of the camera. The pixel velocities are usually obtained from optical flow algorithms, both dense and sparse flow can be used to compute the flow between images and `duv` computed by dividing the flow by the time interval between the images.
Ptr< UnscentedKalmanFilter > | createAugmentedUnscentedKalmanFilter (const AugmentedUnscentedKalmanFilterParams &params)
| Augmented Unscented Kalman Filter factory method.
Ptr< UnscentedKalmanFilter > | createUnscentedKalmanFilter (const UnscentedKalmanFilterParams &params)
| Unscented Kalman Filter factory method.