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Visual tracking via geometric particle filtering on the affine group with optimal importance functions

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3 Author(s)
Junghyun Kwon ; Dept. of EECS, Seoul Nat. Univ., Seoul, South Korea ; Kyoung Mu Lee ; Park, F.C.

We propose a geometric method for visual tracking, in which the 2-D affine motion of a given object template is estimated in a video sequence by means of coordinate-invariant particle filtering on the 2-D affine group Aff(2). Tracking performance is further enhanced through a geometrically defined optimal importance function, obtained explicitly via Taylor expansion of a principal component analysis based measurement function on Aff(2). The efficiency of our approach to tracking is demonstrated via comparative experiments.

Published in:

Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on

Date of Conference:

20-25 June 2009

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