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

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 geo-metrically defined optimal importance function, obtained explicitly via Taylor expansion of a principal component analysis based measurement function on Aff(2). The effi-ciency of our approach to tracking is demonstrated via com-parative experiments. 1