| Presentation | 2011-11-25 Face recognition based on separable lattice 2-D HMMs with variational Bayesian method Kei SAWADA, Akira TAMAMORI, Kei HASHIMOTO, Yoshihiko NANKAKU, Keiichi TOKUDA, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | This paper proposes an image recognition technique based on separable lattice 2-D hidden Markov models (SL2D-HMMs) with the variational Bayesian method. SL2D-HMMs have been proposed to reduce the effect of geometric variations, e.g., size and location. The maximum likelihood criterion had previously been used for training SL2D-HMMs. However, since it is difficult to use sufficient amounts of training data in many image recognition tasks, and it suffered from the over-fitting problem. A higher generalization ability based on model marginalization is expected by applying the Bayesian criterion and useful prior information on model parameters can be utilized as prior distributions. Experiments on face recognition indicated that the proposed method improved image recognition. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | face recognition / hidden Markov models / separable lattice 2-D HMMs / Bayesian criterion / variational Bayesian method |
| Paper # | PRMU2011-120 |
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| Conference Information | |
| Committee | PRMU |
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| Conference Date | 2011/11/17(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 | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Face recognition based on separable lattice 2-D HMMs with variational Bayesian method |
| Sub Title (in English) | |
| Keyword(1) | face recognition |
| Keyword(2) | hidden Markov models |
| Keyword(3) | separable lattice 2-D HMMs |
| Keyword(4) | Bayesian criterion |
| Keyword(5) | variational Bayesian method |
| 1st Author's Name | Kei SAWADA |
| 1st Author's Affiliation | Department of Scientific and Engineering Simulation, Nagoya Institute of Technology() |
| 2nd Author's Name | Akira TAMAMORI |
| 2nd Author's Affiliation | Department of Scientific and Engineering Simulation, Nagoya Institute of Technology |
| 3rd Author's Name | Kei HASHIMOTO |
| 3rd Author's Affiliation | Department of Scientific and Engineering Simulation, Nagoya Institute of Technology |
| 4th Author's Name | Yoshihiko NANKAKU |
| 4th Author's Affiliation | Department of Scientific and Engineering Simulation, Nagoya Institute of Technology |
| 5th Author's Name | Keiichi TOKUDA |
| 5th Author's Affiliation | Department of Scientific and Engineering Simulation, Nagoya Institute of Technology |
| Date | 2011-11-25 |
| Paper # | PRMU2011-120 |
| Volume (vol) | vol.111 |
| Number (no) | 317 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |