OpenCV  3.4.20
Open Source Computer Vision
Public Member Functions | List of all members
cv::TrackerFeatureSet Class Reference

Class that manages the extraction and selection of features. More...

#include <opencv2/tracking/tracker.hpp>

Public Member Functions

 TrackerFeatureSet ()
 
 ~TrackerFeatureSet ()
 
bool addTrackerFeature (String trackerFeatureType)
 Add TrackerFeature in the collection. Return true if TrackerFeature is added, false otherwise. More...
 
bool addTrackerFeature (Ptr< TrackerFeature > &feature)
 
void extraction (const std::vector< Mat > &images)
 Extract features from the images collection. More...
 
const std::vector< Mat > & getResponses () const
 Get the responses. More...
 
const std::vector< std::pair< String, Ptr< TrackerFeature > > > & getTrackerFeature () const
 Get the TrackerFeature collection (TrackerFeature name, TrackerFeature pointer) More...
 
void removeOutliers ()
 Remove outliers for all feature types (optional) More...
 
void selection ()
 Identify most effective features for all feature types (optional) More...
 

Detailed Description

Class that manages the extraction and selection of features.

[189] Feature Extraction and Feature Set Refinement (Feature Processing and Feature Selection). See table I and section III C [132] Appearance modelling -> Visual representation (Table II, section 3.1 - 3.2)

TrackerFeatureSet is an aggregation of TrackerFeature

See also
TrackerFeature

Constructor & Destructor Documentation

◆ TrackerFeatureSet()

cv::TrackerFeatureSet::TrackerFeatureSet ( )

◆ ~TrackerFeatureSet()

cv::TrackerFeatureSet::~TrackerFeatureSet ( )

Member Function Documentation

◆ addTrackerFeature() [1/2]

bool cv::TrackerFeatureSet::addTrackerFeature ( String  trackerFeatureType)

Add TrackerFeature in the collection. Return true if TrackerFeature is added, false otherwise.

Parameters
trackerFeatureTypeThe TrackerFeature name

The modes available now:

  • "HAAR" – Haar Feature-based

The modes that will be available soon:

  • "HOG" – Histogram of Oriented Gradients features
  • "LBP" – Local Binary Pattern features
  • "FEATURE2D" – All types of Feature2D

Example TrackerFeatureSet::addTrackerFeature : :

//sample usage:
Ptr<TrackerFeature> trackerFeature = new TrackerFeatureHAAR( HAARparameters );
featureSet->addTrackerFeature( trackerFeature );
//or add CSC sampler with default parameters
//featureSet->addTrackerFeature( "HAAR" );
Note
If you use the second method, you must initialize the TrackerFeature

◆ addTrackerFeature() [2/2]

bool cv::TrackerFeatureSet::addTrackerFeature ( Ptr< TrackerFeature > &  feature)

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Parameters
featureThe TrackerFeature class

◆ extraction()

void cv::TrackerFeatureSet::extraction ( const std::vector< Mat > &  images)

Extract features from the images collection.

Parameters
imagesThe input images

◆ getResponses()

const std::vector<Mat>& cv::TrackerFeatureSet::getResponses ( ) const

Get the responses.

Note
Be sure to call extraction before getResponses Example TrackerFeatureSet::getResponses : :

◆ getTrackerFeature()

const std::vector<std::pair<String, Ptr<TrackerFeature> > >& cv::TrackerFeatureSet::getTrackerFeature ( ) const

Get the TrackerFeature collection (TrackerFeature name, TrackerFeature pointer)

◆ removeOutliers()

void cv::TrackerFeatureSet::removeOutliers ( )

Remove outliers for all feature types (optional)

◆ selection()

void cv::TrackerFeatureSet::selection ( )

Identify most effective features for all feature types (optional)


The documentation for this class was generated from the following file: