| Presentation | 2007-12-13 Linear and Nonlinear Hybrid Kernel Mutual Subspace method for Object Recognition Hitoshi SAKANO, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | We propose new member of mutual subspace method (MSM) family named linear and nonlinear hybrid kernel mutual subspace method (HKMS) for object recognition. We already proposed kernelized nonlinear version of MSM named KMS. Experimentally, effectiveness of KMS is demonstrated in object recognition problem. However, from the phenomenological view point, origin of effectiveness is unclear, because of properties of recognition data stream is differ from training data stream. When we consider object recognition problem invariant against pose change, training data include various pose object images, and recognition data stream consist by similar images each other. Therefore training data stream has strong nonlinear structure and recognition data stream has approximate linear structure. KMS is not natural since KMS represent such data as same kernel parameter. To solve this problem we propose HKMS, that consist of kernel principal component learning and linear-nonlinear hybrid recognition algorithms. The experiment using artificial data show the effectiveness of HKMS. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | object recognition / subspace method / kernel PCA / mutual subspace method / kernel mutual subspace method |
| Paper # | PRMU2007-143 |
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| Conference Information | |
| Committee | PRMU |
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| Conference Date | 2007/12/6(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
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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) | Linear and Nonlinear Hybrid Kernel Mutual Subspace method for Object Recognition |
| Sub Title (in English) | |
| Keyword(1) | object recognition |
| Keyword(2) | subspace method |
| Keyword(3) | kernel PCA |
| Keyword(4) | mutual subspace method |
| Keyword(5) | kernel mutual subspace method |
| 1st Author's Name | Hitoshi SAKANO |
| 1st Author's Affiliation | NTT Data Corp.() |
| Date | 2007-12-13 |
| Paper # | PRMU2007-143 |
| Volume (vol) | vol.107 |
| Number (no) | 384 |
| Page | pp.pp.- |
| #Pages | 4 |
| Date of Issue | |