Please use this identifier to cite or link to this item:
Title: Constructing PCA baseline algorithms to reevaluate ICA-based face-recognition performance
Authors: Yang, J
Zhang, DD 
Yang, JY
Keywords: Face recognition
Feature extraction
Image representation
Independent component analysis (ICA)
Principal component analysis (PCA)
Issue Date: Aug-2007
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics, Aug. 2007, v. 37, no. 4, p.1015-1021 How to cite?
Journal: IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics 
Abstract: The literature on independent component analysis (ICA)-based face recognition generally evaluates its performance using standard principal component analysis (PCA) within two architectures, ICA Architecture I and ICA Architecture II. In this correspondence, we analyze these two ICA architectures and find that ICA Architecture I involves a vertically centered PCA process (PCA I), while ICA Architecture II involves a whitened horizontally centered PCA process (PCA II). Thus, it makes sense to use these two PCA versions as baselines to reevaluate the performance of ICA-based face-recognition systems. Experiments on the FERET, AR, and AT&T face-image databases showed no significant differences between ICA Architecture I (II) and PCA I (II), although ICA Architecture I (or II) may, in some cases, significantly outperform standard PCA. It can be concluded that the performance of ICA strongly depends on the PCA process that it involves. Pure ICA projection has only a trivial effect on performance in face recognition.
ISSN: 1083-4419
DOI: 10.1109/TSMCB.2007.891541
Rights: © 2007 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.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
SMCB_C_37_4_07.pdf271.64 kBAdobe PDFView/Open
View full-text via PolyU eLinks SFX Query
Show full item record
PIRA download icon_1.1View/Download Contents


Last Week
Last month
Citations as of Feb 16, 2019


Last Week
Last month
Citations as of Feb 15, 2019

Page view(s)

Last Week
Last month
Citations as of Feb 17, 2019


Citations as of Feb 17, 2019

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.