tailieunhanh - Báo cáo hóa học: " Research Article Monocular 3D Tracking of Articulated Human Motion in Silhouette and Pose Manifolds"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Monocular 3D Tracking of Articulated Human Motion in Silhouette and Pose Manifolds | Hindawi Publishing Corporation EURASIP Journal on Image and Video Processing Volume 2008 Article ID 326896 18 pages doi 2008 326896 Research Article Monocular 3D Tracking of Articulated Human Motion in Silhouette and Pose Manifolds Feng Guo1 and Gang Qian1 2 1 Department of Electrical Engineering Arizona State University Tempe AZ 85287-9309 USA 2 Arts Media and Engineering Program Department of Electrical Engineering Arizona State University Tempe AZ 85287-8709 USA Correspondence should be addressed to Gang Qian Received 1 February 2007 Revised 24 July 2007 Accepted 29 January 2008 Recommended by Nikos Nikolaidis 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 lowdimensional 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. Copyright 2008 F. Guo and G. 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. 1. INTRODUCTION Reliable recovery and tracking of articulated human motion from video are considered a very challenging problem in computer vision due to the versatility of human