Kernel Discriminant Embedding in face recognition
In this paper, we present a novel and effective feature extraction technique for face recognition. The proposed technique incorporates a kernel trick with Graph Embedding and the Fisher's criterion which we call it as Kernel Discriminant Embedding (KDE). The proposed technique projects the orig...
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| Format: | Article |
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2011
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| Online Access: | http://shdl.mmu.edu.my/3340/ |
| _version_ | 1848790300720365568 |
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| author | Han, Pang Ying Jin, Andrew Teoh Beng Toh Kar, Ann |
| author_facet | Han, Pang Ying Jin, Andrew Teoh Beng Toh Kar, Ann |
| author_sort | Han, Pang Ying |
| building | MMU Institutional Repository |
| collection | Online Access |
| description | In this paper, we present a novel and effective feature extraction technique for face recognition. The proposed technique incorporates a kernel trick with Graph Embedding and the Fisher's criterion which we call it as Kernel Discriminant Embedding (KDE). The proposed technique projects the original face samples onto a low dimensional subspace such that the within-class face samples are minimized and the between-class face samples are maximized based on Fisher's criterion. The implementation of kernel trick and Graph Embedding criterion on the proposed technique reveals the underlying structure of data. Our experimental results on face recognition using ORL, FRGC and FERET databases validate the effectiveness of KDE for face feature extraction. (C) 2011 Elsevier Inc. All rights reserved. |
| first_indexed | 2025-11-14T18:10:26Z |
| format | Article |
| id | mmu-3340 |
| institution | Multimedia University |
| institution_category | Local University |
| last_indexed | 2025-11-14T18:10:26Z |
| publishDate | 2011 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | mmu-33402012-01-09T04:01:09Z http://shdl.mmu.edu.my/3340/ Kernel Discriminant Embedding in face recognition Han, Pang Ying Jin, Andrew Teoh Beng Toh Kar, Ann QA75.5-76.95 Electronic computers. Computer science In this paper, we present a novel and effective feature extraction technique for face recognition. The proposed technique incorporates a kernel trick with Graph Embedding and the Fisher's criterion which we call it as Kernel Discriminant Embedding (KDE). The proposed technique projects the original face samples onto a low dimensional subspace such that the within-class face samples are minimized and the between-class face samples are maximized based on Fisher's criterion. The implementation of kernel trick and Graph Embedding criterion on the proposed technique reveals the underlying structure of data. Our experimental results on face recognition using ORL, FRGC and FERET databases validate the effectiveness of KDE for face feature extraction. (C) 2011 Elsevier Inc. All rights reserved. 2011 Article PeerReviewed Han, Pang Ying and Jin, Andrew Teoh Beng and Toh Kar, Ann (2011) Kernel Discriminant Embedding in face recognition. Journal of Visual Communication and Image Representation, 22 (7). pp. 634-642. ISSN 10473203 http://dx.doi.org/10.1016/j.jvcir.2011.07.009 doi:10.1016/j.jvcir.2011.07.009 doi:10.1016/j.jvcir.2011.07.009 |
| spellingShingle | QA75.5-76.95 Electronic computers. Computer science Han, Pang Ying Jin, Andrew Teoh Beng Toh Kar, Ann Kernel Discriminant Embedding in face recognition |
| title | Kernel Discriminant Embedding in face recognition |
| title_full | Kernel Discriminant Embedding in face recognition |
| title_fullStr | Kernel Discriminant Embedding in face recognition |
| title_full_unstemmed | Kernel Discriminant Embedding in face recognition |
| title_short | Kernel Discriminant Embedding in face recognition |
| title_sort | kernel discriminant embedding in face recognition |
| topic | QA75.5-76.95 Electronic computers. Computer science |
| url | http://shdl.mmu.edu.my/3340/ http://shdl.mmu.edu.my/3340/ http://shdl.mmu.edu.my/3340/ |