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Face representation using independent component analysis

✍ Scribed by Pong C. Yuen; J.H. Lai

Publisher: Elsevier Science
Year: 2002
Tongue: English
Weight: 510 KB
Volume: 35
Category: Article
ISSN: 0031-3203
DOI: 10.1016/s0031-3203(01)00101-7

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✦ Synopsis

This paper addresses the problem of face recognition using independent component analysis (ICA). More speciÿcally, we are going to address two issues on face representation using ICA. First, as the independent components (ICs) are independent but not orthogonal, images outside a training set cannot be projected into these basis functions directly. In this paper, we propose a least-squares solution method using Householder Transformation to ÿnd a new representation. Second, we demonstrate that not all ICs are useful for recognition. Along this direction, we design and develop an IC selection algorithm to ÿnd a subset of ICs for recognition. Three public available databases, namely, MIT AI Laboratory, Yale University and Olivette Research Laboratory, are selected to evaluate the performance and the results are encouraging.

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