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Robust Visual Tracking using Search Area Estimation and Multi-channel Local Edge Pattern

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2017, 22(7), pp.47-54
  • DOI : 10.9708/jksci.2017.22.07.047
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : May 29, 2017
  • Accepted : July 23, 2017
  • Published : July 31, 2017

Eun-Joon Kim 1

1국방과학연구소

Accredited

ABSTRACT

Recently, correlation filter based trackers have shown excellent tracking performance and computational efficiency. In order to enhance tracking performance in the correlation filter based tracker, search area which is image patch for finding target must include target. In this paper, two methods to discriminatively represent target in the search area are proposed. Firstly, search area location is estimated using pyramidal Lucas-Kanade algorithm. By estimating search area location before filtering, fast motion target can be included in the search area. Secondly, we investigate multi-channel Local Edge Pattern(LEP) which is insensitive to illumination and noise variation. Qualitative and quantitative experiments are performed with eight dataset, which includes ground truth. In comparison with method without search area estimation, our approach retain tracking for the fast motion target. Additionally, the proposed multi-channel LEP improves discriminative performance compare to existing features.

Citation status

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