Name
Title | ||
|---|---|---|
Learning 3D Spatiotemporal Gait Feature by Convolutional Network for Person Identification |
Abstract | ||
|---|---|---|
•An efficient deep learning-based person identification method for visual biometric.•A hierarchical descriptive-geometric 3D gait feature extraction scheme.•A compact-size DCNN with multiple stacks of asymmetric convolutional filters.•Outperformance of identification rate with state-of-the-art approaches.•Comparable performance with several modern CNNs. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.neucom.2020.02.048 | Neurocomputing |
Keywords | DocType | Volume |
3D Gait recognition,Person identification,Deep convolutional neural network,Spatiotemporal gait information | Journal | 397 |
ISSN | Citations | PageRank |
0925-2312 | 4 | 0.45 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Thien Huynh-The | 1 | 94 | 21.54 |
| Cam-Hao Hua | 2 | 45 | 11.22 |
| Tu Anh T. Nguyen | 3 | 56 | 9.27 |
| Dong-Seong Kim | 4 | 64 | 28.80 |