Singular Value Decomposition based Particle Filter for Tracking in Complex Environment

Y. Huang and X. Luo (PRC)


Singular value decomposition, particle filter, Bhat tacharyya coefficient


Tracking in complex environment is an important and chal lenging problem. Most of the existing methods adopt low level features derived from objects appearance. In contrast to this mainstream approach, this paper introduces a new method considering image as matrix then employing singu lar value as the features. For evaluating the likelihood be tween template and the candidate, which is weight update in particle filter, we offer Bhattacharyya coefficient based metrics. We compare our proposed algorithm with typi cal color histogram based particle filter in two challenges: confusing color in background and illumination change. Experiment results show that our approach achieves better tracking accuracy and robustness.

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