Mean-Shift Tracking Using Fuzzy Coding Histogram

نویسندگان

  • Huaping Liu
  • Liuyang Wang
  • Fuchun Sun
چکیده

In this paper, the fuzzy coding histogram representation for an image region is proposed for visual tracking. At the initial frame, we use the fuzzy clustering technology on all pixels within the initial detection box to get the cluster prototypes, which are used to construct the fuzzy codebook. During the tracking period, the candidate image region is also represented by a fuzzy coding histogram which is constructed by the fuzzy memberships. This representation can incorporate more feature information and enhance the tracking robustness. In addition, we use the cumulative distribution function between the fuzzy coding histograms to construct a cross-bin metric and use the mean-shift iteration to realize the robust visual tracking. Finally, some tracking experimental results are presented to demonstrate the effectiveness of the proposed approach.

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تاریخ انتشار 2014