This paper presents an approach to human motion tracking using multiple pre-trained activity models for propagation of particles in Annealed Particle Filtering. Hidden Markov models are trained on dimensionally reduced joint angle data to produce models of activity. Particles are divided between models for propagation by HMM synthesis, before converging on a solution during the annealing process. The approach facilitates multi-view tracking of unknown subjects performing multiple known activities with low particle numbers.
Published in19th International Conference on Pattern Recognition (ICPR 2008)
19TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1-6
Pages3125 - 3128 (4)
CitationDARBY, J., LI, B. and COSTEN, N., 2008. Behaviour based particle filtering for human articulated motion tracking. 19th International Conference on Pattern Recognition (ICPR 2008), Tampa, FL, 8th-11th December 2008, pp.3125 -3128
VersionAM (Accepted Manuscript)
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