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Proceedings Paper

Face recognition based on eigen-illumination scheme and uncorrelated discriminant analysis
Author(s): Danghui Liu; LanSun Shen; Kin-Man Lam
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Paper Abstract

The illumination changes on face images make face recognition a very difficult task. In this paper, a human face representation scheme that is insensitive to illumination variation is proposed in order to deal with the problem. The variations in lighting over human faces are modeled by means of Principal Component Analysis (PCA) on a number of blurred faces under different lighting conditions. Then the 'difference image', which is the difference between the original image and the reconstructed image, is used for face recognition. We also propose an uncorrelated Linear Discriminant Analysis technique for face recognition based on the eigen-illumination representation scheme. This method can obtain the uncorrelated optimal discriminant vectors (UODVs) so that the extracted features are uncorrelated. Experimental results show that the proposed method is effective to deal with varying illimunation problem for face recognition.

Paper Details

Date Published: 31 July 2006
PDF: 8 pages
Proc. SPIE 5960, Visual Communications and Image Processing 2005, 59602G (31 July 2006); doi: 10.1117/12.631561
Show Author Affiliations
Danghui Liu, Beijing Univ. of Technology (China)
The Academy of Equipment, Command and Technology (China)
LanSun Shen, Beijing Univ. of Technology (China)
Kin-Man Lam, The Hong Kong Polytechnic Univ. (Hong Kong China)


Published in SPIE Proceedings Vol. 5960:
Visual Communications and Image Processing 2005
Shipeng Li; Fernando Pereira; Heung-Yeung Shum; Andrew G. Tescher, Editor(s)

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