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http://hdl.handle.net/10397/224
| Title: | A novel face recognition system using hybrid neural and dual eigenspaces methods | Authors: | Zhang, DD Peng, H Zhou, J Pal, SK |
Issue Date: | Nov-2002 | Source: | IEEE transactions on systems, man, and cybernetics. Part A, Systems and humans, Nov. 2002, v. 32, no. 6, p. 787-793 | Abstract: | In this paper, we present an automated face recognition (AFR) system that contains two components: eye detection and face recognition. Based on invariant radial basis function (IRBF) networks and knowledge rules of facial topology, a hybrid neural method is proposed to localize human eyes and segment the face region from a scene. A dual eigenspaces method (DEM) is then developed to extract algebraic features of the face and perform the recognition task with a two-layer minimum distance classifier. Experimental results illustrate that the proposed system is effective and robust. | Keywords: | Dual eigenspaces method Eyes detection Face recognition Hybrid neural method |
Publisher: | Institute of Electrical and Electronics Engineers | Journal: | IEEE transactions on systems, man, and cybernetics. Part A, Systems and humans | ISSN: | 1083-4427 | EISSN: | 1083-4419 | DOI: | 10.1109/TSMCA.2003.808252 | Rights: | © 2002 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 |
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|---|---|---|---|---|
| SMCA_SH_32_6_02.pdf | 1.08 MB | Adobe PDF | View/Open |
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