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http://dx.doi.org/10.3745/KIPSTB.2011.18B.1.011

Key Pose-based Proposal Distribution for Upper Body Pose Tracking  

Oh, Chi-Min (전남대학교 전자컴퓨터공학부)
Lee, Chil-Woo (전남대학교 전자컴퓨터공학부)
Publication Information
The KIPS Transactions:PartB / v.18B, no.1, 2011 , pp. 11-20 More about this Journal
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.
Keywords
Upper Body Pose; Pictorial Structures; Particle Filter; Proposal Distribution; Key Poses;
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1 E. A. Wan and R. van der Merwe, "The Unscented Kalman Filter for Nonlinear Estimation", Adaptive Systems for Signal Processing, Communications, and Control Symposium, pp. 153-158, 2000.   DOI
2 Borgefors and Gunilla "Hierearchical Chamfer Matching: A Parametric Edge Matching Algorithm", IEEE Trans. Pattern Anal. Mach. Intell., Vol. 6, pp. 849-865, Nov 1988.   DOI   ScienceOn
3 R. Kindermann and J. L. Snell, "Markov Random Fields and Their Applications", American Mathematical Society, Providence, RI, 1980.
4 K. Nishiyama, "Fast and Effective Generation of the Proposal distribution for Particle filters", Vol 85(12), pp. 2412-2417, 2005.   DOI   ScienceOn
5 J. Bourgain, On Lipschitz, "Embeddings of Finite Metric Spaces in Hilbert Space", Israel Journal of Mathematics, Vol. 52, pp. 46-52, 1985.   DOI
6 N. A. Setiawan, S. J. Hong, J. W. Kim and C. W. Lee, "Gaussian Mixture Model in Improved HLS Color Space for Human Silhouette Extraction", Int. Conf. Artificial Reality and Telexistence, pp. 732-741, 2006.
7 A. Agarwal and B. Triggs, "A Local Basis Representation for Estimating Human Pose from Cluttered Images", Asian Conf. Computer Vision, pp. 50-59, 2006.
8 O. Freifeld, A. Weiss, S. Zuffi and M. J. Black, "Contour People: A Parameterized Model of 2D Articulated Human Shape", In Int. Conf. Computer Vision and Pattern Recognition, pp. 639-646, 2010.   DOI
9 S. Maskell, "A Tutorial on Particle Filters for On-line Nonlinear/Non-Gaussian Bayesian Tracking", IEEE Trans. Signal Processing, Vol. 50, No. 2, pp. 174-188, 2002.   DOI   ScienceOn
10 K. M. Manson, "Markov Chain Monte Carlo Posterior Sampling with the Hamiltonian method", Proc. Sensitivity Analysis of Model Output, pp. 456-467, 2001.   DOI
11 M. W. Lee and I. Cohen, "Proposal Maps driven MCMC for Estimating Human Body Pose in Static Images", In Int. Conf. Computer Vision and Pattern Recognition, vol. 2, pp.334-341, 2004.   DOI
12 K. Okuma A. Taleghani N. de Freitas J. Little and D. Lowe, "A Boosted Particle Filter: Multitarget Detection and Tracking", European Conf. Computer Vision, pp. 28-39, 2004.
13 S. X. Ju, M. J. Black and Y. Yacoob, "Cardboard People: A Parameterized Model of Articulated Image Motion", Int. Conf. Automatic Face and Gesture Recognition, pp. 38-44, 1996.   DOI
14 Makoto Kato, Yen-Wei Chen and Gang Xu, "Articulated hand tracking by pca-ica approach", Int. Conf. Automatic Face and Gesture Recognition, pp. 329-334, 2006   DOI
15 H. G. Barrow, J. M. Tenenbaum, R. C. Bolles and H. C. Wolf, "Parametric Correspondence and Chamfer Matching: Two New Technique for Image Matching", Int. Conf. Artificial Intelligence, pp. 1175-1177, 1997.
16 X. Zhang, C. Li, X. Tong, W. Hu, S. Maybank, and Y. Zhang, "Efficient human pose estimation via parsing a tree structure based human model", Int. Conf. Computer Vision, pp. 1349-1356, 2009.   DOI
17 M. Andriluka, S. Roth and B. Schilele, "Pictorial Structures Revisited:People Detection and Articulated Pose Estimation", Int. Conf. Computer Vision & Pattern Recognition, pp.1014-1021, 2009.   DOI
18 H. Jiang, "Human Pose Estimation Using Consistent Max-Covering", Int. Conf. Computer Vision, pp.1357-1364, 2009.   DOI