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Object tracking based on particle filter with discriminative features

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Abstract

This paper presents a particle filter-based visual tracking method with online feature selection mechanism. In color-based particle filter algorithm the weights of particles do not always represent the importance correctly, this may cause that the object tracking based on particle filter converge to a local region of the object. In our proposed visual tracking method, the Bhattacharyya distance and the local discrimination between the object and background are used to define the weights of the particles, which can solve the existing local convergence problem. Experiments demonstrates that the proposed method can work well not only in single object tracking processes but also in multiple similar objects tracking processes.

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Authors and Affiliations

  1. Key Laboratory of Autonomous Systems and Networked Control (Ministry of Education), South China University of Technology, Guangzhou Guangdong, 510640, China

    Yunji Zhao & Hailong Pei

Authors
  1. Yunji Zhao
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  2. Hailong Pei
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Corresponding author

Correspondence to Hailong Pei.

Additional information

This work was supported by the Natural Science Foundation of China (Nos. 60736024, 61174053), the Cultivation Fund of the Key Scientific and Technical Innovation Project, Ministry of Education of China (No. 708069), and the Specialized Research Fund for the Doctoral Program of Higher Education (No. 20100172110023).

Yunji ZHAO received his M.S. degree from School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China, in 2008. Currently, he is pursuing his Ph.D. degree at College of Automation Science and Engineering, South China University of Technology. His research interests include visual navigation and real-time tracking.

Hailong PEI received his B.S. and M.S. degrees from Northwestern Polytechnical University, in 1986 and in 1989, respectively. He received his Ph.D. degree from College of Automation Science and Engineering, South China University of Technology, Guangzhou, China, in 1992. He was a postdoctoral fellow at the Chinese University of Hong Kong from 1997 to 1998. He worked as a senior visiting scholar at Carnegie Mellon University from 1999 to 2001. His research interests include robot control, nonlinear control, embedded system, computer numerical control system, and artificial neural network.

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Zhao, Y., Pei, H. Object tracking based on particle filter with discriminative features. J. Control Theory Appl. 11, 42–53 (2013). https://doi.org/10.1007/s11768-013-1088-0

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  • DOI: https://doi.org/10.1007/s11768-013-1088-0

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