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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Huiyu Zhou Schaefer, G. |
| Copyright Year | 2010 |
| Description | Author affiliation: Queen's University Belfast, U.K. (Huiyu Zhou) || Loughborough University, U.K. (Schaefer, G.) |
| Abstract | Face recognition is an important part of many computer vision applications. In this paper, we present a face recognition algorithm based on semantic feature extraction and tensor subspace analysis. The semantic features we employ include eyes and mouth, plus the region outlined by the three weight centres of the edges between them. We then evaluate these features using tensor subspace analysis. Singular value decomposition is used to solve the eigenvector problem and to project the geometrical properties to the face manifold. Experimental results demonstrate that our proposed algorithm performs well, and that it is capable of achieving more accurate convergence coupled with a lower computational demand compared to standard approaches. |
| Starting Page | 33 |
| Ending Page | 36 |
| File Size | 373747 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424463718 |
| ISSN | 13342630 |
| e-ISBN | 9781424463732 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-09-15 |
| Publisher Place | Croatia |
| Access Restriction | Subscribed |
| Rights Holder | ELMAR (Electronics in Marines) |
| Subject Keyword | Training tensor subspace analysis Tensile stress Face recognition Semantics feature extraction Mouth Feature extraction Face semantic features |
| Content Type | Text |
| Resource Type | Article |
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