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Human Body Motion Tracking Using ICP and Particle Filter  

Kim, Dae-Hwan (POSTECH 컴퓨터공학과)
Kim, Hyo-Jung (KR 미래기술연구소 기술기획담당)
Kim, Dai-Jin (POSTECH 컴퓨터공학과)
Publication Information
Journal of KIISE:Software and Applications / v.36, no.12, 2009 , pp. 977-985 More about this Journal
Abstract
This paper proposes a real-time algorithm for tracking the fast moving human body. Although Iterative closest point (ICP) algorithm is suitable for real-time tracking due to its efficiency and low computational complexity, ICP often fails to converge when the human body moves fast because the closest point may be mistakenly selected and trapped in a local minimum. To overcome such limitation, we combine a particle filter based on a motion history information with the ICP. The proposed human body motion tracking algorithm reduces the search space for each limb by employing a hierarchical tree structure, and enables tracking of the fast moving human bodies by using the motion prediction based on the motion history. Experimental results show that the proposed human body motion tracking provides accurate tracking performance and fast convergence rate.
Keywords
Human body motion tracking; ICP; particle filter; motion history information; human body model;
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