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Cooperative fusion particle filter tracker

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Abstract

Robust visual tracking has become an important topic in the field of computer vision. Integrating multiple cues has proved to be a promising approach to visual tracking in situations where no single cue is suitable. In this work, a new particle filter based visual tracking algorithm is proposed. By introducing a new cooperative fusion strategy, the proposed tracker has better fault tolerance ability than the traditional methods. Experiments are performed in various tracking scenes to evaluate the proposed algorithm, and the results show improved tracking accuracy.

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Authors and Affiliations

  1. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China

    LingFeng Wang & ChunHong Pan

  2. College of Information and Engineering, China University of Geosciences, Beijing, 100083, China

    HongPing Yan

Authors
  1. LingFeng Wang
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  2. HongPing Yan
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  3. ChunHong Pan
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Corresponding author

Correspondence to LingFeng Wang.

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Wang, L., Yan, H. & Pan, C. Cooperative fusion particle filter tracker. Sci. China Inf. Sci. 57, 1–14 (2014). https://doi.org/10.1007/s11432-013-4853-2

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  • DOI: https://doi.org/10.1007/s11432-013-4853-2

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