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An Efficient Particle Filter–based Tracking Method Using Graphics Processing Unit (GPU)

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Abstract

Particle filter has been proven very robust in handling non-linear and non-Gaussian problems and has been widely used in the area of object tracking. One of the main problems in particle filter-based object tracking is, however, its high computational cost induced by the most time-consuming stage of measurement model computation. This paper makes progress in resolving the problem by proposing an efficient particle filter-based tracking algorithm using color information. First, a compact color cooccurrence histogram is presented, which considers both spatial and color information and can effectively represent color distribution with a very small number of histogram bins. The paper also introduces integral images by which the cooccurrence histogram can be obtained with simple array reference operations. However, the construction of the integral images on the CPU may be computationally expensive. Hence, this paper develops parallel algorithms on a desktop Graphics Processing Unit (GPU), which accomplishes the integral images construction and cooccurrence histogram computation after bin index determination. The resulting algorithm is quite efficient and has better performance than the traditional histogram-based tracking algorithm. The tracking time of the proposed algorithm increases insignificantly with the growth of particle number, and it remains consistent among varying image sequences and stable throughout all frames in the same image sequence due to its irrelevance to object size. Experiments in diverse image sequences validate our conclusions.

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Acknowledgements

We highly appreciate the insightful comments of the reviewers which improve both the quality and presentation of the manuscript. The research was supported by the National Natural Science Foundation of China (60973080, 61170149 and 60673110), Program for New Century Excellent Talents in University from Chinese Ministry of Education (NCET-10-0151), Key Project by Chinese Ministry of Education (No. 210063). It was also supported in part by the Program for New Century Excellent Talents of Heilongjiang Province (1153-NCET-002) and High-level professionals (innovative teams) of Heilongjiang University (Hdtd2010-07).

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    Peihua Li

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Li, P. An Efficient Particle Filter–based Tracking Method Using Graphics Processing Unit (GPU). J Sign Process Syst 68, 317–332 (2012). https://doi.org/10.1007/s11265-011-0620-z

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