Wavelet moments for recognizing human body posture from 3D scans

Werghi, N. and Xiao, Y. (2002) Wavelet moments for recognizing human body posture from 3D scans. In: 16th International Conference on Pattern Recognition., Québec, Canada, 11-15 August 2002, pp. 319-322. ISBN 9780769516967 (doi: 10.1109/ICPR.2002.1044704)

Abstract

This paper addresses the problem of recognizing a human body (HB) posture from a cloud of 3D points acquired by a human body scanner It suggests the wavelet transform coefficients (WTC) as 3D shape descriptors of the HB posture. The WTC showed to have a high discrimination power between posture classes. Integrated within a Bayesian classification framework and compared with other standard moments, the WTC showed great capabilities in discriminating between close postures. The qualities of the WTC features were also reflected on its classification rate, ranked first when compared with other 3D features.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Xiao, Mr Yijun
• Authors: Werghi, N., and Xiao, Y.
• Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
• College/School: College of Science and Engineering > School of Computing Science
• Publisher: Institute of Electrical and Electronics Engineers
• ISBN: 9780769516967
• Copyright Holders: Copyright © 2002 Institute of Electrical and Electronics Engineers
• First Published: First published in Proceedings of the 16th International Conference on Pattern Recognition
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher