| Presentation | 2010-10-08 Gait-based Person Identification Robust against Speed Variation using CHLAC features and HMMs AQMAR Muhammad RASYID, Koichi SHINODA, Sadaoki FURUI, |
|---|---|
| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | The performance of gait-based person identification is strongly affected by the variations in walking speed. In our previous study, we have proposed a new framework that is robust against speed variation across gait sequences, which combines the Fisher discriminant analysis (FDA)-based cubic higher-order local auto-correlation (CHLAC) features and the statistical framework provided by hidden Markov models (HMMs). The CHLAC features capture the within-phase spatio-temporal characteristics of each walker, while the HMMs identify the person and the phase of each gait even when the walking speed changes nonlinearly. However, since CHLAC features do not have much shape information of a gait phase, it is difficult to identify/segment the walking phase accurately. Therefore in this paper, we not only use CHLAC features to train the HMM, but also utilize principal component analysis (PCA) features that have more shape information of a gait phase in order to have a better gait cycle segmentation/alignment process. We also evaluate our method when the walking speed varied within a gait sequence by manually creating mixed speed variation data within a gait sequence in TokyoTech database. We compared our method with other conventional methods using three other public databases. The proposed method was better than the others when the speed varied across and within a gait sequence. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | CHLAC / FDA / PCA / Gaussian Mixture HMMs |
| Paper # | PRMU2010-92,SP2010-48,WIT2010-36 |
| Date of Issue |
| Conference Information | |
| Committee | WIT |
|---|---|
| Conference Date | 2010/10/1(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 | Well-being Information Technology(WIT) |
|---|---|
| Language | ENG |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Gait-based Person Identification Robust against Speed Variation using CHLAC features and HMMs |
| Sub Title (in English) | |
| Keyword(1) | CHLAC |
| Keyword(2) | FDA |
| Keyword(3) | PCA |
| Keyword(4) | Gaussian Mixture HMMs |
| 1st Author's Name | AQMAR Muhammad RASYID |
| 1st Author's Affiliation | Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology() |
| 2nd Author's Name | Koichi SHINODA |
| 2nd Author's Affiliation | Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology |
| 3rd Author's Name | Sadaoki FURUI |
| 3rd Author's Affiliation | Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology |
| Date | 2010-10-08 |
| Paper # | PRMU2010-92,SP2010-48,WIT2010-36 |
| Volume (vol) | vol.110 |
| Number (no) | 221 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |