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CVPR
2009
IEEE

Visual tracking on the affine group via geometric particle filtering using optimal importance function

11 years 7 months ago
Visual tracking on the affine group via geometric particle filtering using optimal importance function
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 coordinateinvariant 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.
Junghyun Kwon (Seoul National University), Kyoung
Added 22 Apr 2009
Updated 02 Apr 2010
Type Conference
Year 2009
Where CVPR
Authors Junghyun Kwon (Seoul National University), Kyoung Mu Lee (Seoul National University), Frank Park (Seoul National University)
Comments (1)
Junghyun_Kwon.jpgMATLAB code available
[0]

The MATLAB code and video data for this CVPR 2009 paper are availabe at "http://cv.snu.ac.kr/jhkwon/tracking".
The MATALB code is only for implementing the proposed idea, and not optimized for computation speed.
I hope this MATALB code wil be useful to the tracking researchers.

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