Name
Abstract | ||
|---|---|---|
In the gait recognition community, silhouette-based gait representations such as gait energy image have been widely employed for the last decade. In order to obtain good quality of gait features, it is essential to get a well aligned silhouette sequence, which is, however, not necessarily easy with imperfect silhouettes and also with scale and position changes due to perspective projection. We therefore propose a gait recognition-oriented approach to pedestrian trajectory extraction, i. e., bounding box sequence for each pedestrian. More specifically, we firstly developed an inter-active tool to get camera calibration parameters for a target scene geometry without on-site workload. We then introduce a geometric constraint to better keep the consistency of bounding boxes among frames w.r.t. the pedestrian ’s height and foot bottom points on the ground plane. Sub-sequently, we apply analytical dynamic programing (DP) repeatedly to find multiple pedestrian ’s trajectories on the ground plane, where data and transition scores are computed based on semantic segmentation results and color histogram similarity. Moreover, since DP just considers the smoothness between adjacent frames, we approximate the trajectory by a piece-wise linear trajectory to make it more globally smooth. Experimental results show that the proposed method enables us to make better aligned gait features and consequently improves gait recognition accuracy. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/BTAS.2018.8698559 | 2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS) |
Field | DocType | ISSN |
Computer vision,Color histogram,Segmentation,Silhouette,Computer science,Perspective (graphical),Camera resectioning,Artificial intelligence,Trajectory,Bounding overwatch,Minimum bounding box | Conference | 2474-9680 |
ISBN | Citations | PageRank |
978-1-5386-7180-1 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yasushi Makihara | 1 | 1012 | 70.67 |
| Gakuto Ogi | 2 | 0 | 0.34 |
| Yasushi Yagi | 3 | 1752 | 186.22 |