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Proceedings Paper

Video object tracking using improved chamfer matching and condensation particle filter
Author(s): Tao Wu; Xiaoqing Ding; Shengjin Wang; Kongqiao Wang
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Paper Abstract

Object tracking is an essential problem in the field of video and image processing. Although tracking algorithms working on gray video are convenient in actual applications, they are more difficult to be developed than those using color features, since less information is taken into account. Few researches have been dedicated to tracking object using edge information. In this paper, we proposed a novel video tracking algorithm based on edge information for gray videos. This method adopts the combination of a condensation particle filter and an improved chamfer matching. The improved chamfer matching is rotation invariant and capable of estimating the shift between an observed image patch and a template by an orientation distance transform. A modified discriminative likelihood measurement method that focuses on the difference is adopted. These values are normalized and used as the weights of particles which predict and track the object. Experiment results show that our modifications to chamfer matching improve its performance in video tracking problem. And the algorithm is stable, robust, and can effectively handle rotation distortion. Further work can be done on updating the template to adapt to significant viewpoint and scale changes of the appearance of the object during the tracking process.

Paper Details

Date Published: 26 February 2008
PDF: 10 pages
Proc. SPIE 6813, Image Processing: Machine Vision Applications, 681304 (26 February 2008); doi: 10.1117/12.766388
Show Author Affiliations
Tao Wu, Tsinghua Univ. (China)
Xiaoqing Ding, Tsinghua Univ. (China)
Shengjin Wang, Tsinghua Univ. (China)
Kongqiao Wang, Nokia Research Ctr. (China)

Published in SPIE Proceedings Vol. 6813:
Image Processing: Machine Vision Applications
Kurt S. Niel; David Fofi, Editor(s)

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