Title

View-Invariant Recognition Of Body Pose From Space-Time Templates

Abstract

We propose a new template-based approach for view-invariant recognition of body poses, based on geometric constraints derived from the motion of body point triplets. In addition to spatial information our templates encode temporal information of body pose transitions. Unlike existing methods that study a body pose as a whole, we decompose it into a number of body point triplets, and compare their motions to our templates. Using the fact that the homography induced by the motion of a triplet of body points in two identical body pose transitions reduces to the special case of a homology, we exploit the equality of two of its eigenvalues to impose constraints on the similarity of the pose transitions between two subjects, observed by different perspective cameras and from different viewpoints. Extensive experimental results show that our method can accurately identify human poses from video sequences when they are observed from totally different viewpoints with different camera parameters. ©2008 IEEE.

Publication Date

9-23-2008

Publication Title

26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR

Number of Pages

-

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/CVPR.2008.4587795

Socpus ID

51949089822 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/51949089822

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