16th International Conference on Pattern Recognition (ICPR'02) - Volume 1 Wavelet Moments for Recognizing Human Body Posture from 3D Scans Quebec City, QC, Canada August 11-August 15 ISBN: 0-7695-1695-X
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.
Citation:
Naoufel Werghi, Yijun Xiao, "Wavelet Moments for Recognizing Human Body Posture from 3D Scans," icpr, vol. 1, pp.10319, 16th International Conference on Pattern Recognition (ICPR'02) - Volume 1, 2002 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||