On Image Analysis by the Methods of Moments
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
3-D Moment Forms: Their Construction and Application to Object Identification and Positioning
IEEE Transactions on Pattern Analysis and Machine Intelligence
Invariant Image Recognition by Zernike Moments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Pattern recognition with moment invariants: a comparative study and new results
Pattern Recognition
Explicit formulae for polyhedra moments
Pattern Recognition Letters
Wavelet Moments for Recognizing Human Body Posture from 3D Scans
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
Machine Vision and Applications - Special issue: Human modeling, analysis, and synthesis
Made-to-Measure Technologies for an Online Clothing Store
IEEE Computer Graphics and Applications
Three-Dimensional Moment Invariants
IEEE Transactions on Pattern Analysis and Machine Intelligence
The wavelet transform, time-frequency localization and signal analysis
IEEE Transactions on Information Theory
Skin colour segmentation based 2D and 3D human pose modelling using Discrete Wavelet Transform
Pattern Recognition and Image Analysis
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This paper deals with the recognition of human body postures from a cloud of 3D points acquired by a human body scanner. Motivated by finding a representation that embodies a high power of discrimination between posture classes, a new type of 3D shape descriptors is suggested, namely wavelet transform coefficients (WC). These features can be seen as an extension to 3D of the 2D wavelet shape descriptors developed by (Shen, D., Ip, H.H.S., 1999. Pattern Recognition, 32, 151-165). The WC is compared with other 3D shape descriptors, within a Bayesian classification framework. Experiments with real scan data show that the WC outperforms other standard 3D shape descriptors in terms of discrimination power and classification rate.