the KCF (Kernelized Correlation Filter) tracker  
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#include <opencv2/tracking.hpp>
the KCF (Kernelized Correlation Filter) tracker 
KCF is a novel tracking framework that utilizes properties of circulant matrix to enhance the processing speed. This tracking method is an implementation of [108] which is extended to KCF with color-names features ([51]). The original paper of KCF is available at http://www.robots.ox.ac.uk/~joao/publications/henriques_tpami2015.pdf as well as the matlab implementation. For more information about KCF with color-names features, please refer to http://www.cvl.isy.liu.se/research/objrec/visualtracking/colvistrack/index.html. 
◆ FeatureExtractorCallbackFN
      
        
          | typedef void(* cv::TrackerKCF::FeatureExtractorCallbackFN) (const Mat, const Rect, Mat &) | 
      
 
 
◆ MODE
Feature type to be used in the tracking grayscale, colornames, compressed color-names The modes available now: 
- "GRAY" – Use grayscale values as the feature
- "CN" – Color-names feature 
 
 
◆ TrackerKCF()
  
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          | cv::TrackerKCF::TrackerKCF | ( |  | ) |  |  | protected | 
 
 
◆ ~TrackerKCF()
  
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          | virtual cv::TrackerKCF::~TrackerKCF | ( |  | ) |  |  | virtual | 
 
 
◆ create()
| Python: | 
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|  | cv.TrackerKCF_create( | [, parameters] | ) -> | retval | 
 
Create KCF tracker instance. 
- Parameters
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◆ setFeatureExtractor()
The documentation for this class was generated from the following file: