Optimized particles for 3-D tracking

Authors:
Huiying Chen;Youfu Li
Affiliations:
Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong;Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong, Kowloon, Hong Kong
Venue:
ICIRA'10 Proceedings of the Third international conference on Intelligent robotics and applications - Volume Part I
Year:
2010

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Abstract

3-D visual tracking is useful for many of its applications. In this paper, we propose two different ways for different system configurations to optimize particle filter for enhancing 3-D tracking performances. On one hand, a new data fusion method is proposed to obtain the optimal importance density function for active vision systems. On the other hand, we develop a method for reconfigurable vision systems to maximize the effective sampling size in particle filter, which consequentially helps to solve the degeneracy problem and minimize the tracking error.