Adaptive mean shift and particle filter tracking method based on joint feature

La Zhang; Yingyun Yang; Huabing Wang; Yansi Yang; Bo Liu

doi:10.1117/12.2010754

14 March 2013 Adaptive mean shift and particle filter tracking method based on joint feature

La Zhang, Yingyun Yang, Huabing Wang, Yansi Yang, Bo Liu

Proceedings Volume 8768, International Conference on Graphic and Image Processing (ICGIP 2012); 87681A (2013) https://doi.org/10.1117/12.2010754
Event: 2012 International Conference on Graphic and Image Processing, 2012, Singapore, Singapore

Abstract

In the object tracking area, both particle filter and mean shift algorithm have proven successful approaches. However, both of them have notable weakness. In this paper, we present a new algorithm which combined the two algorithms to track the target. First, the mean shift algorithm is employed to search an object candidate near the target state. Then, if the candidate is good enough, it will be used to adapt the particle filter parameters, including the number of particle filter, and etc. Finally, the particle filter will estimate the target state based on these new parameters. Further, the paper introduces the color-texture combined feature instead of color feature.

Citation Download Citation

La Zhang, Yingyun Yang, Huabing Wang, Yansi Yang, and Bo Liu "Adaptive mean shift and particle filter tracking method based on joint feature", Proc. SPIE 8768, International Conference on Graphic and Image Processing (ICGIP 2012), 87681A (14 March 2013); https://doi.org/10.1117/12.2010754

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