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Title: Is ICA significantly better than PCA for face recognition?
Authors: Yang, J
Zhang, DD 
Yang, JY
Issue Date: 2005
Source: Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV’05)
Abstract: The standard PCA was always used as baseline algorithm to evaluate ICA-based face recognition systems in the previous research. In this paper, we examine the two architectures of ICA for image representation and find that ICA Architecture I involves a PCA process by vertically centering (PCA I), while ICA Architecture II involves a whitened PCA process by horizontally centering (PCA II). So, it is reasonable to use these two PCA versions as baseline algorithms to revaluate the ICA-based face recognition systems. The experiments were performed on the FERET face database. The experimental results show there is no significant performance differences between ICA Architecture I (II) and PCA I (II), although ICA Architecture II significantly outperforms the standard PCA. It can be concluded that the performance of ICA strongly depends on its involved PCA process. The pure ICA projection has little effect on the performance of face recognition.
Keywords: Face recognition
Principal component analysis
Independent component analysis
ICA architecture
Publisher: IEEE
ISSN: 1550-5499
Rights: © 2005 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
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