Visual Tracking via Particle Filtering on the Affine Group

Authors:
Junghyun Kwon;Frank C. Park
Affiliations:
School of Electrical Engineering and Computer Science, Seoul National University, Seoul 151-742, Korea;School of Mechanical and Aerospace Engineering, Seoul National University, Seoul 151-742, Korea
Venue:
International Journal of Robotics Research
Year:
2010

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Abstract

We present a particle filtering algorithm for visual tracking, in which the state equations for the object motion evolve on the two-dimensional affine group. We first formulate, in a coordinate-invariant and geometrically meaningful way, particle filtering on the affine group that allows for combined stateâ聙聰covariance estimation. Measurement likelihoods are also calculated from the image covariance descriptors using incremental principal geodesic analysis, a generalization of principal component analysis to curved spaces. Comparative visual tracking studies demonstrate the increased robustness of our tracking algorithm.