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

Junghyun Kwon, Kyoung Mu Lee, Frank C. Park
2009 2009 IEEE Conference on Computer Vision and Pattern Recognition  
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
more » ... ia comparative experiments. Compared with the version of CVPR 09 Proceedings, note that some corrections are made to the notational error (eq. 14) and the terminology error (state prediction density --> state transition density).
doi:10.1109/cvpr.2009.5206501 dblp:conf/cvpr/KwonLP09 fatcat:hj7zv6trzraphpsckod6crrfke