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Proceedings Paper

Recognition of faces using texture-based principal component analysis and Grassmannian distances analysis
Author(s): Bei Ma; Hailin Zhang
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Paper Abstract

This paper introduces a new face recognition method-texture-based Principal Component Analysis (PCA), which employs PCA on texture features.Initially, the eigenspace of texture images is created by eigenvalues and eigenvectors.From this space,the eigentextures are constructed,and most of the eigentextures are selected by using PCA.With these eigentextures, we generalize Grassmannian distances into texture feature space to recognize.We address the problem of face recognition in terms of the subject-specific subspaces instead of image vectors.The proposed method is tested on Essex Face 94 database,and it has been demenstrated to have a promising performance.

Paper Details

Date Published: 1 October 2011
PDF: 8 pages
Proc. SPIE 8285, International Conference on Graphic and Image Processing (ICGIP 2011), 82856C (1 October 2011); doi: 10.1117/12.913468
Show Author Affiliations
Bei Ma, Xidian Univ. (China)
Hailin Zhang, Xidian Univ. (China)

Published in SPIE Proceedings Vol. 8285:
International Conference on Graphic and Image Processing (ICGIP 2011)
Yi Xie; Yanjun Zheng, Editor(s)

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