Name
Abstract | ||
|---|---|---|
Time-to-collision can be directly measured from a spatio-temporal image sequence obtained from an uncalibrated camera. This it would appear to offer a simple, elegant measurement for use in obstacle avoidance. However, previous techniques for computing time to collision from an optical flow have proven impractical for real applications. This paper present a new approach for computing time to collision (TTC) based on the idea of measuring the rate of change of the "intrinsic scale". Intrinsic scale is a geometric invariant that is valid at most points in an image, and can be rapidly determined using a multi-resolution pyramid. In this paper we develop the approach and demonstrate its feasibility by comparing the results with range measurements obtained from a laser ranging device on a moving vehicle. Experimental results show that this is a simple method to obtain reliable TTC with a low computational cost. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/978-3-540-77457-0_8 | Springer Tracts in Advanced Robotics |
Keywords | Field | DocType |
real time,optical flow,obstacle avoidance,rate of change | Obstacle avoidance,Computer vision,Simulation,Time to collision,Artificial intelligence,Engineering,Optical flow,Laplacian pyramid,Image sequence | Conference |
Volume | ISSN | Citations |
39 | 1610-7438 | 19 |
PageRank | References | Authors |
0.92 | 10 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Amaury Nègre | 1 | 124 | 8.88 |
| Christophe Braillon | 2 | 55 | 5.10 |
| James L. Crowley | 3 | 3209 | 1274.79 |
| Christian Laugier | 4 | 271 | 18.03 |