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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Furui Liu Xiyan Liu |
| Copyright Year | 2012 |
| Description | Author affiliation: College of Computer Science and Information Engineering, Chongqing Technology and Business University, Chongqing, P. R. China (Xiyan Liu) || State Key Lab of CAD&CG, College of Computer Science, Zhejiang University, Zheda Road 38, Hangzhou P. R. China (Furui Liu) |
| Abstract | This paper proposes two novel methods. First we propose Locality Enhanced Spectral Embedding(LESE) which can make a locality preserving mapping from the original nearest neighbor graph to the real line. It uses a regularized non-nearest penalty based on a non-nearest neighbor graph to enhance the locality of the mapping result. Second we make an efficient method for face recognition task. Previous methods consider a p1 × p2 image as a high dimensional vector in $R^{p1×p2}$ space and the pixels of each image are considered independent. It fails to consider that a face image is intrinsically a matrix, the pixels spatially close to each other may also be correlated. To explicitly model the spatial locality, we propose a novel Spatially Smooth Spectral Regression(SSR). It is a two stage framework for subspace learning, sequentially SSR uses the LESE to generate an eigenspace, and it solves a Laplacian smoothing penalty regularized regression to construct the projective function and learn a spatially smooth subspace. The subspace forms a good representation of the original face image. Experimrntal results on face recognition demonstrate the effecttiveness of our proposed algorithm. |
| Starting Page | 299 |
| Ending Page | 303 |
| File Size | 570772 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781467322386 |
| e-ISBN | 9781467322379 |
| e-ISBN | 9781467322362 |
| DOI | 10.1109/ICInfA.2012.6246822 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-06-06 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Laplace equations Smoothing methods Accuracy Face recognition regression Educational institutions Vectors Spectral embedding Face spatially smooth |
| Content Type | Text |
| Resource Type | Article |
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