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

Kwon Junghyun | Zendy; Kyoung Mu Lee | Zendy; F.C. Park | Zendy

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

Author(s) -

Kwon Junghyun,

Kyoung Mu Lee,

F.C. Park

Publication year - 2009

Publication title -

2009 ieee conference on computer vision and pattern recognition

Language(s) - English

Resource type - Conference proceedings

DOI - 10.1109/cvprw.2009.5206501

Subject(s) - affine transformation , affine shape adaptation , tracking (education) , particle filter , harris affine region detector , invariant (physics) , video tracking , computer vision , artificial intelligence , eye tracking , affine coordinate system , computer science , mathematics , affine group , affine combination , object (grammar) , filter (signal processing) , affine space , geometry , psychology , pedagogy , mathematical physics

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.

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