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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Qubo You Nanning Zheng Shaoyi Du Yang Wu |
| Copyright Year | 2006 |
| Description | Author affiliation: Inst. of Artificial Intelligence & Robotics, Xi'an Jiaotong Univ. (Qubo You; Nanning Zheng; Shaoyi Du; Yang Wu) |
| Abstract | We propose a novel manifold learning approach, called neighborhood discriminant projection (NDP), for robust face recognition. The purpose of NDP is to preserve the within-class neighboring geometry of the image space, while keeping away the projected vectors of the samples of different classes. For representing the intrinsic within-class neighboring geometry and the similarity of the samples of different classes, the within-class affinity weight and the between-class affinity weight are used to model the within-class submanifold and the between-class submanifold of the samples, respectively. Several experiments on face recognition are conducted to demonstrate the effectiveness and robustness of our proposed method |
| Sponsorship | IEEE CPS |
| Starting Page | 532 |
| Ending Page | 535 |
| File Size | 413371 |
| Page Count | 4 |
| File Format | |
| ISBN | 0769525210 |
| ISSN | 10514651 |
| DOI | 10.1109/ICPR.2006.853 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-08-20 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Face recognition Geometry Image reconstruction Robustness Principal component analysis Linear discriminant analysis Pattern recognition Artificial intelligence Intelligent robots Orbital robotics |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition |
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