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

Content Provider	Springer Nature Link
Author	Li, Peihua
Copyright Year	2011
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.
Starting Page	317
Ending Page	332
Page Count	16
File Format	PDF
ISSN	19398018
Journal	Journal of Signal Processing Systems
Volume Number	68
Issue Number	3
e-ISSN	19398115
Language	English
Publisher	Springer US
Publisher Date	2011-09-14
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Image processing Particle filter Color model Integral images Graphics Processing Unit (GPU) Signal, Image and Speech Processing Computer Imaging, Vision, Pattern Recognition and Graphics Pattern Recognition Electrical Engineering Circuits and Systems Image Processing and Computer Vision
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Signal Processing Control and Systems Engineering Information Systems Modeling and Simulation Hardware and Architecture

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