Recognition of faces using texture-based principal component analysis and Grassmannian distances analysis

Bei Ma; Hailin Zhang

doi:10.1117/12.913468

1 October 2011 Recognition of faces using texture-based principal component analysis and Grassmannian distances analysis

Bei Ma, Hailin Zhang

Author Affiliations +

Proceedings Volume 8285, International Conference on Graphic and Image Processing (ICGIP 2011); 82856C (2011) https://doi.org/10.1117/12.913468
Event: 2011 International Conference on Graphic and Image Processing, 2011, Cairo, Egypt

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.

Citation Download Citation

Bei Ma and Hailin Zhang "Recognition of faces using texture-based principal component analysis and Grassmannian distances analysis", Proc. SPIE 8285, International Conference on Graphic and Image Processing (ICGIP 2011), 82856C (1 October 2011); https://doi.org/10.1117/12.913468

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