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Proceedings Paper

Multi-information fusion for human motion tracking by particle filter
Author(s): Ming Du; Ling Guan
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Paper Abstract

Human motion analysis research, especially the human tracking part, remains a challenging task by far. The difficulties lie in several aspects: self-occlusion, high dimensionality of parameter space and the gap between high-level image understanding and low-level image features etc. In our work we use particle filter to track human movement from monocular video sequences with an articulated human body model. We fuse region, color and boundary information to build a robust measurement function. Among them, the boundary information represented by Fourier Descriptors (FD) sets up a new and effective connection between the estimated model parameters and the image likelihoods. Compared with the previously used boundary or contour cue, FD has many noticeable advantages. Moreover, we introduce an adaptive property into the particle filter for more robust state propagation and measurement updating. Our method is shown to work effectively in experiments.

Paper Details

Date Published: 24 June 2005
PDF: 11 pages
Proc. SPIE 5960, Visual Communications and Image Processing 2005, 59600H (24 June 2005); doi: 10.1117/12.631536
Show Author Affiliations
Ming Du, Ryerson Univ. (Canada)
Ling Guan, Ryerson Univ. (Canada)

Published in SPIE Proceedings Vol. 5960:
Visual Communications and Image Processing 2005
Shipeng Li; Fernando Pereira; Heung-Yeung Shum; Andrew G. Tescher, Editor(s)

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