Name
Abstract | ||
|---|---|---|
To assist visually impaired people, a variety of obstacle detection (OD) methods with the monocular vision have been developed. Most conventional OD methods detect the obstacle by using the variation of the motion vector or the object size between two consecutive image frames. However, the OD performance using the short-term variation is significantly affected by the tracking error, which leads to inaccurate OD results. To cope with this problem, this paper presents a novel OD method based on a new structure, called Deformable Grid (DG). The DG is initially a regular gridshaped, but it can be deformed gradually depending on the motion of the object in the scene. The proposed method detects the object at risk of collision based on the degree of the deformation of the DG. Experimental results demonstrate that the proposed OD method outperforms the conventional ones in terms of processing time as well as accuracy. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/TCE.2015.7298298 | IEEE Transactions on Consumer Electronics |
Keywords | Field | DocType |
Cameras,Image edge detection,Iron,Shape,Robustness,Sensors,Accuracy | Monocular vision,Obstacle,Computer vision,Collision detection,Computer science,Collision,Robustness (computer science),Artificial intelligence,Grid,Tracking error,Motion vector | Journal |
Volume | Issue | ISSN |
61 | 3 | 0098-3063 |
Citations | PageRank | References |
8 | 0.51 | 19 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| muncheon kang | 1 | 26 | 6.79 |
| sungho chae | 2 | 14 | 3.75 |
| jeeyoung sun | 3 | 16 | 3.45 |
| JinWoo Yoo | 4 | 8 | 0.51 |
| Sung-Jea Ko | 5 | 1051 | 114.34 |