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| Received:April 25, 2011Revised:January 10, 2012 |
| 基金项目: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). |
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| Object tracking based on particle filter with discriminative features |
| Yunji ZHAO,Hailong PEI |
| (Key Laboratory of Autonomous Systems and Networked Control (Ministry of Education), South China University of Technology) |
| 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. |
| Key words: Histogram of oriented gradients Local discrimination Particle filter Multiple object tracking |
