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This contribution changes the way how trackers should be implemented by
programmer. It should be noted first, that from the user prospective,
Tracker::create() method still can be called with the same effect.
However, there's no more thing as a "constructor" for Tracker, they
should be created via static functions, e.g.
static Ptr<TrackerMIL> createTracker(const TrackerMIL::Params ¶meters=TrackerMIL::Params());
From the programmer's perspective now for every tracker what is declared
in tracker.hpp header is more a "interface", while the real
implementation class can (and has to) be implemented in .cpp file.
Changes in documentation are also included.
121 lines
4.0 KiB
ReStructuredText
121 lines
4.0 KiB
ReStructuredText
Tracker Algorithms
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==================
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.. highlight:: cpp
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The following algorithms are implemented at the moment.
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.. [MIL] B Babenko, M-H Yang, and S Belongie, Visual Tracking with Online Multiple Instance Learning, In CVPR, 2009
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.. [OLB] H Grabner, M Grabner, and H Bischof, Real-time tracking via on-line boosting, In Proc. BMVC, volume 1, pages 47– 56, 2006
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TrackerBoosting
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---------------
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This is a real-time object tracking based on a novel on-line version of the AdaBoost algorithm.
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The classifier uses the surrounding background as negative examples in update step to avoid the drifting problem. The implementation is based on
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[OLB]_.
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.. ocv:class:: TrackerBoosting
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Implementation of TrackerBoosting from :ocv:class:`Tracker`::
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class CV_EXPORTS_W TrackerBoosting : public Tracker
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{
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public:
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void read( const FileNode& fn );
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void write( FileStorage& fs ) const;
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static Ptr<trackerBoosting> createTracker(const trackerBoosting::Params ¶meters=trackerBoosting::Params());
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virtual ~trackerBoosting(){};
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protected:
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bool initImpl( const Mat& image, const Rect2d& boundingBox );
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bool updateImpl( const Mat& image, Rect2d& boundingBox );
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};
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TrackerBoosting::Params
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-----------------------------------------------------------------------
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.. ocv:struct:: TrackerBoosting::Params
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List of BOOSTING parameters::
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struct CV_EXPORTS Params
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{
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Params();
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int numClassifiers; //the number of classifiers to use in a OnlineBoosting algorithm
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float samplerOverlap; //search region parameters to use in a OnlineBoosting algorithm
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float samplerSearchFactor; // search region parameters to use in a OnlineBoosting algorithm
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int iterationInit; //the initial iterations
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int featureSetNumFeatures; // #features
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void read( const FileNode& fn );
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void write( FileStorage& fs ) const;
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};
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TrackerBoosting::createTracker
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-----------------------------------------------------------------------
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Constructor
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.. ocv:function:: Ptr<trackerBoosting> TrackerBoosting::createTracker(const trackerBoosting::Params ¶meters=trackerBoosting::Params())
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:param parameters: BOOSTING parameters :ocv:struct:`TrackerBoosting::Params`
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TrackerMIL
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----------
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The MIL algorithm trains a classifier in an online manner to separate the object from the background. Multiple Instance Learning avoids the drift problem for a robust tracking. The implementation is based on [MIL]_.
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Original code can be found here http://vision.ucsd.edu/~bbabenko/project_miltrack.shtml
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.. ocv:class:: TrackerMIL
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Implementation of TrackerMIL from :ocv:class:`Tracker`::
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class CV_EXPORTS_W TrackerMIL : public Tracker
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{
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public:
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void read( const FileNode& fn );
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void write( FileStorage& fs ) const;
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static Ptr<trackerMIL> createTracker(const trackerMIL::Params ¶meters=trackerMIL::Params());
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virtual ~trackerMIL(){};
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protected:
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bool initImpl( const Mat& image, const Rect2d& boundingBox );
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bool updateImpl( const Mat& image, Rect2d& boundingBox );
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};
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TrackerMIL::Params
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------------------
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.. ocv:struct:: TrackerMIL::Params
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List of MIL parameters::
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struct CV_EXPORTS Params
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{
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Params();
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//parameters for sampler
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float samplerInitInRadius; // radius for gathering positive instances during init
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int samplerInitMaxNegNum; // # negative samples to use during init
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float samplerSearchWinSize; // size of search window
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float samplerTrackInRadius; // radius for gathering positive instances during tracking
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int samplerTrackMaxPosNum; // # positive samples to use during tracking
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int samplerTrackMaxNegNum; // # negative samples to use during tracking
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int featureSetNumFeatures; // # features
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void read( const FileNode& fn );
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void write( FileStorage& fs ) const;
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};
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TrackerMIL::createTracker
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-------------------------------
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Constructor
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.. ocv:function:: Ptr<trackerMIL> TrackerMIL::createTracker(const trackerMIL::Params ¶meters=trackerMIL::Params())
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:param parameters: MIL parameters :ocv:struct:`TrackerMIL::Params`
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