Visual tracking via geometric particle filtering on the affine group with optimal importance functions
Kwon Junghyun, Kyoung Mu Lee, Frank C. Park · 2009 IEEE Conference on Computer Vision and Pattern Recognition · 2009
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.