Presentation | 2011-05-19 Higher Order Orthogonal Iteration vs. Multilinear Principle Component Analysis for Tensor Subspace Learning Guifang DUAN, Yen-Wei CHEN, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Tensor subspace learning has been of great interest in computer vision and pattern recognition applications. In this paper, we demonstrate the relationship Higher Order Orthogonal Iteration (HOOI) and Multilinear Principle Component Analysis (MPCA), which are two of the most fundamental and most popular techniques for tensor subspace learning. We also mathematically prove that MPCA is a special case of HOOI and investigate the performance of HOOR on face recognition. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | High Order Orthogonal Iteration (HOOI) / Multilinear Principle Component Analysis (MPCA) / Tensor subspace learning / Face recognition |
Paper # | IE2011-12,PRMU2011-4,MI2011-4 |
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Conference Information | |
Committee | PRMU |
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Conference Date | 2011/5/12(1days) |
Place (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Pattern Recognition and Media Understanding (PRMU) |
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Language | ENG |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Higher Order Orthogonal Iteration vs. Multilinear Principle Component Analysis for Tensor Subspace Learning |
Sub Title (in English) | |
Keyword(1) | High Order Orthogonal Iteration (HOOI) |
Keyword(2) | Multilinear Principle Component Analysis (MPCA) |
Keyword(3) | Tensor subspace learning |
Keyword(4) | Face recognition |
1st Author's Name | Guifang DUAN |
1st Author's Affiliation | University Research Organization of Science and Engineering, Ritsumeikan University() |
2nd Author's Name | Yen-Wei CHEN |
2nd Author's Affiliation | College of Information Science and Engineering, Ritsumeikan |
Date | 2011-05-19 |
Paper # | IE2011-12,PRMU2011-4,MI2011-4 |
Volume (vol) | vol.111 |
Number (no) | 48 |
Page | pp.pp.- |
#Pages | 6 |
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