EURASIP Journal on Image and Video Processing
Volume 2008 (2008), Article ID 326896, 18 pages
doi:10.1155/2008/326896
Research Article
Monocular 3D Tracking of Articulated Human Motion in Silhouette and Pose Manifolds
1Department of Electrical Engineering, Arizona State University, Tempe, AZ 85287-9309, USA
2Arts, Media and Engineering Program, Department of Electrical Engineering, Arizona State University, Tempe, AZ 85287-8709, USA
Received 1 February 2007; Revised 24 July 2007; Accepted 29 January 2008
Academic Editor: Nikos Nikolaidis
Copyright © 2008 Feng Guo and Gang Qian. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
This paper presents a robust computational framework for monocular 3D tracking of human movement. The main innovation of the proposed framework is to explore the underlying data structures of the body silhouette and pose spaces by constructing low-dimensional silhouettes and poses manifolds, establishing intermanifold mappings, and performing tracking in such manifolds using a particle filter. In addition, a novel vectorized silhouette descriptor is introduced to achieve low-dimensional, noise-resilient silhouette representation. The proposed articulated motion tracker is view-independent, self-initializing, and capable of maintaining multiple kinematic trajectories. By using the learned mapping from the silhouette manifold to the pose manifold, particle sampling is informed by the current image observation, resulting in improved sample efficiency. Decent tracking results have been obtained using synthetic and real videos.