Key Pose-based Proposal Distribution for Upper Body Pose Tracking 


Vol. 18,  No. 1, pp. 11-20, Feb.  2011
10.3745/KIPSTB.2011.18.1.11


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  Abstract

Pictorial Structures is known as an effective method that recognizes and tracks human poses. In this paper, the upper body pose is also tracked by PS and a particle filter(PF). PF is one of dynamic programming methods. But Markov chain-based dynamic motion model which is used in dynamic programming methods such as PF, couldn`t predict effectively the highly articulated upper body motions. Therefore PF often fails to track upper body pose. In this paper we propose the key pose-based proposal distribution for proper particle prediction based on the similarities between key poses and an upper body silhouette. In the experimental results we confirmed our 70.51% improved performance comparing with a conventional method.

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[IEEE Style]

C. M. Oh and C. W. Lee, "Key Pose-based Proposal Distribution for Upper Body Pose Tracking," The KIPS Transactions:PartB , vol. 18, no. 1, pp. 11-20, 2011. DOI: 10.3745/KIPSTB.2011.18.1.11.

[ACM Style]

Chi Min Oh and Chil Woo Lee. 2011. Key Pose-based Proposal Distribution for Upper Body Pose Tracking. The KIPS Transactions:PartB , 18, 1, (2011), 11-20. DOI: 10.3745/KIPSTB.2011.18.1.11.

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