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Proceedings Paper

Real time tracking by LOPF algorithm with mixture model
Author(s): Bo Meng; Ming Zhu; Guangliang Han; Zhiguo Wu
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Paper Abstract

A new particle filter-the Local Optimum Particle Filter (LOPF) algorithm is presented for tracking object accurately and steadily in visual sequences in real time which is a challenge task in computer vision field. In order to using the particles efficiently, we first use Sobel algorithm to extract the profile of the object. Then, we employ a new Local Optimum algorithm to auto-initialize some certain number of particles from these edge points as centre of the particles. The main advantage we do this in stead of selecting particles randomly in conventional particle filter is that we can pay more attentions on these more important optimum candidates and reduce the unnecessary calculation on those negligible ones, in addition we can overcome the conventional degeneracy phenomenon in a way and decrease the computational costs. Otherwise, the threshold is a key factor that affecting the results very much. So here we adapt an adaptive threshold choosing method to get the optimal Sobel result. The dissimilarities between the target model and the target candidates are expressed by a metric derived from the Bhattacharyya coefficient. Here, we use both the counter cue to select the particles and the color cur to describe the targets as the mixture target model. The effectiveness of our scheme is demonstrated by real visual tracking experiments. Results from simulations and experiments with real video data show the improved performance of the proposed algorithm when compared with that of the standard particle filter. The superior performance is evident when the target encountering the occlusion in real video where the standard particle filter usually fails.

Paper Details

Date Published: 15 November 2007
PDF: 6 pages
Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 678623 (15 November 2007); doi: 10.1117/12.749350
Show Author Affiliations
Bo Meng, Changchun Institute of Optics, Fine Mechanics and Physics (China)
Graduate School of the Chinese Academy of Sciences (China)
Ming Zhu, Changchun Institute of Optics, Fine Mechanics and Physics (China)
Guangliang Han, Changchun Institute of Optics, Fine Mechanics and Physics (China)
Zhiguo Wu, Changchun Institute of Optics, Fine Mechanics and Physics (China)
Graduate School of the Chinese Academy of Sciences (China)


Published in SPIE Proceedings Vol. 6786:
MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition

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