Detail of Publication
| Text Language | English |
|---|---|
| Authors | Masakazu Iwamura, Shunsuke Mori, Koichiro Nakamura, Takuya Tanoue, Yuzuko Utsumi, Yasushi Makihara, Daigo Muramatsu, Koichi Kise, and Yasushi Yagi |
| Title | Individuality-preserving Silhouette Extraction for Gait Recognition and Its Speedup |
| Journal | IEICE Transactions on Information and Systems |
| Vol. | E104-D |
| No. | 7 |
| Pages | pp.992-1001 |
| Reviewed or not | Reviewed |
| Month & Year | July 2021 |
| Abstract | Most gait recognition approaches rely on silhouette-based representations due to high recognition accuracy and computational efficiency. A fundamental problem for those approaches is how to extract individuality-preserved silhouettes from real scenes accurately. Foreground colors may be similar to background colors, and the background is cluttered. Therefore, we propose a method of individuality-preserving silhouette extraction for gait recognition using standard gait models (SGMs) composed of clean silhouette sequences of various training subjects as shape priors. The SGMs are smoothly introduced into a well-established graph-cut segmentation framework. Experiments showed that the proposed method achieved better silhouette extraction accuracy by more than 2.3% than representative methods and better identification rate of gait recognition (improved by more than 11.0% at rank 20). Besides, to reduce the computation cost, we introduced approximation in the calculation of dynamic programming. As a result, without reducing the segmentation accuracy, we reduced 85.0% of the computational cost. |
| DOI | 10.1587/transinf.2020ZDP7500 |
- Following file is available.
- Entry for BibTeX
@Article{Iwamura2021, author = {Masakazu Iwamura and Shunsuke Mori and Koichiro Nakamura and Takuya Tanoue and Yuzuko Utsumi and Yasushi Makihara and Daigo Muramatsu and Koichi Kise and Yasushi Yagi}, title = {Individuality-preserving Silhouette Extraction for Gait Recognition and Its Speedup}, journal = {IEICE Transactions on Information and Systems}, year = 2021, month = jul, volume = {E104-D}, number = {7}, pages = {992--1001}, DOI = {10.1587/transinf.2020ZDP7500} }