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Proceedings Paper

3D head model classification using optimized EGI
Author(s): Xin Tong; Hau-san Wong; Bo Ma
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Paper Abstract

With the general availability of 3D digitizers and scanners, 3D graphical models have been used widely in a variety of applications. This has led to the development of search engines for 3D models. Especially, 3D head model classification and retrieval have received more and more attention in view of their many potential applications in criminal identifications, computer animation, movie industry and medical industry. This paper addresses the 3D head model classification problem using 2D subspace analysis methods such as 2D principal component analysis (2D PCA[3]) and 2D fisher discriminant analysis (2DLDA[5]). It takes advantage of the fact that the histogram is a 2D image, and we can extract the most useful information from these 2D images to get a good result accordingingly. As a result, there are two main advantages: First, we can perform less calculation to obtain the same rate of classification; second, we can reduce the dimensionality more than PCA to obtain a higher efficiency.

Paper Details

Date Published: 26 January 2006
PDF: 8 pages
Proc. SPIE 6056, Three-Dimensional Image Capture and Applications VII, 60560M (26 January 2006); doi: 10.1117/12.641366
Show Author Affiliations
Xin Tong, City Univ. of Hong Kong (Hong Kong China)
Hau-san Wong, City Univ. of Hong Kong (Hong Kong China)
Bo Ma, City Univ. of Hong Kong (Hong Kong China)


Published in SPIE Proceedings Vol. 6056:
Three-Dimensional Image Capture and Applications VII
Brian D. Corner; Peng Li; Matthew Tocheri, Editor(s)

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