OpenCV  3.0.0
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tracker.hpp File Reference
#include "opencv2/core.hpp"
#include "opencv2/imgproc/types_c.h"
#include "feature.hpp"
#include "onlineMIL.hpp"
#include "onlineBoosting.hpp"
#include <iostream>


struct  cv::TrackerTLD::Params
struct  cv::TrackerMedianFlow::Params
struct  cv::TrackerBoosting::Params
struct  cv::TrackerMIL::Params
struct  cv::TrackerFeatureHAAR::Params
struct  cv::TrackerSamplerPF::Params
 This structure contains all the parameters that can be varied during the course of sampling algorithm. Below is the structure exposed, together with its members briefly explained with reference to the above discussion on algorithm's working. More...
struct  cv::TrackerSamplerCS::Params
struct  cv::TrackerSamplerCSC::Params
class  cv::Tracker
 Base abstract class for the long-term tracker: More...
class  cv::TrackerStateEstimatorAdaBoosting::TrackerAdaBoostingTargetState
 Implementation of the target state for TrackerAdaBoostingTargetState. More...
class  cv::TrackerBoosting
 This is a real-time object tracking based on a novel on-line version of the AdaBoost algorithm. More...
class  cv::TrackerFeature
 Abstract base class for TrackerFeature that represents the feature. More...
class  cv::TrackerFeatureFeature2d
 TrackerFeature based on Feature2D. More...
class  cv::TrackerFeatureHAAR
 TrackerFeature based on HAAR features, used by TrackerMIL and many others algorithms. More...
class  cv::TrackerFeatureHOG
 TrackerFeature based on HOG. More...
class  cv::TrackerFeatureLBP
 TrackerFeature based on LBP. More...
class  cv::TrackerFeatureSet
 Class that manages the extraction and selection of features. More...
class  cv::TrackerMedianFlow
 Median Flow tracker implementation. More...
class  cv::TrackerMIL
 The MIL algorithm trains a classifier in an online manner to separate the object from the background. More...
class  cv::TrackerStateEstimatorMILBoosting::TrackerMILTargetState
class  cv::TrackerModel
 Abstract class that represents the model of the target. It must be instantiated by specialized tracker. More...
class  cv::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  cv::TrackerSamplerAlgorithm
 Abstract base class for TrackerSamplerAlgorithm that represents the algorithm for the specific sampler. More...
class  cv::TrackerSamplerCS
 TrackerSampler based on CS (current state), used by algorithm TrackerBoosting. More...
class  cv::TrackerSamplerCSC
 TrackerSampler based on CSC (current state centered), used by MIL algorithm TrackerMIL. More...
class  cv::TrackerSamplerPF
 This sampler is based on particle filtering. More...
class  cv::TrackerStateEstimator
 Abstract base class for TrackerStateEstimator that estimates the most likely target state. More...
class  cv::TrackerStateEstimatorAdaBoosting
 TrackerStateEstimatorAdaBoosting based on ADA-Boosting. More...
class  cv::TrackerStateEstimatorMILBoosting
 TrackerStateEstimator based on Boosting. More...
class  cv::TrackerStateEstimatorSVM
 TrackerStateEstimator based on SVM. More...
class  cv::TrackerTargetState
 Abstract base class for TrackerTargetState that represents a possible state of the target. More...
class  cv::TrackerTLD
 TLD is a novel tracking framework that explicitly decomposes the long-term tracking task into tracking, learning and detection. More...




#define BOILERPLATE_CODE(name, classname)


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

Macro Definition Documentation

#define BOILERPLATE_CODE (   name,
static Ptr<classname> createTracker(const classname::Params &parameters=classname::Params());\
virtual ~classname(){};