| Presentation | 2003/2/14 The Training Algorithm based on Variational Approximation for Separable 2D-HMM Yasushi OHNO, Yoshihiko NANKAKU, Keiichi TOKUDA, Tadashi KITAMURA, Zoubin GHAHRAMANI, |
|---|---|
| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In image recognition, a variety of elasticity, rotation and shift of image affects recognition performance seriously. To solve this problem, several methods based on 2D-HMM have been proposed. However, since the structure of 2D-HMM is more complex than that of 1D-GMM, high computational cost is required to calculate the likelihood and estimate the model parameters. In this paper, we define separable 2D-HMM which consists of two state sequences : vertical and horizontal sequences, and propose a training algorithm for separable 2D-HMM based on variational approximation. The proposed method can reduce the computational complexity as compared to N-best approximation and the lower bound of log-likelihood is guaranteed to increase at each iteration of the training algorithm |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Hidden Markov Models / 2D-HMM / Variational Approximation / EM Algorithm / Image Recognition |
| Paper # | PRMU2002-211 |
| Date of Issue |
| Conference Information | |
| Committee | PRMU |
|---|---|
| Conference Date | 2003/2/14(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | |
| Vice Chair | |
| Secretary | |
| Assistant | |
| Paper Information | |
| Registration To | Pattern Recognition and Media Understanding (PRMU) |
|---|---|
| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | The Training Algorithm based on Variational Approximation for Separable 2D-HMM |
| Sub Title (in English) | |
| Keyword(1) | Hidden Markov Models |
| Keyword(2) | 2D-HMM |
| Keyword(3) | Variational Approximation |
| Keyword(4) | EM Algorithm |
| Keyword(5) | Image Recognition |
| 1st Author's Name | Yasushi OHNO |
| 1st Author's Affiliation | Dept. of Intelligence and Computer Science, Nagoya Institute of Technology() |
| 2nd Author's Name | Yoshihiko NANKAKU |
| 2nd Author's Affiliation | Dept. of Intelligence and Computer Science, Nagoya Institute of Technology |
| 3rd Author's Name | Keiichi TOKUDA |
| 3rd Author's Affiliation | Dept. of Intelligence and Computer Science, Nagoya Institute of Technology |
| 4th Author's Name | Tadashi KITAMURA |
| 4th Author's Affiliation | Dept. of Intelligence and Computer Science, Nagoya Institute of Technology |
| 5th Author's Name | Zoubin GHAHRAMANI |
| 5th Author's Affiliation | Dept. of Intelligence and Computer Science, Nagoya Institute of Technology |
| Date | 2003/2/14 |
| Paper # | PRMU2002-211 |
| Volume (vol) | vol.102 |
| Number (no) | 652 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |