Name
Abstract | ||
|---|---|---|
This paper addresses the problem of tracking a planar region of the scene using an uncalibrated omnidirectional camera. Omnidirectional cameras are a popular choice of visual sensors in robotics because the large field of view is well adapted to motion estimation and obstacle avoidance. The novelty of this work resides in simplifying the calibration phase by providing a direct approach to tracking without any prior knowledge of the camera, lens or mirror parameters. We deal with a nonlinear optimization problem that can be solved for small displacements between two images like those acquired at video rate by a camera mounted on a robot. In order to assess the performance of the proposed method, we perform experiments with synthetic and real data. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/IROS.2009.5354470 | St. Louis, MO |
Keywords | Field | DocType |
large field,popular choice,uncalibrated central catadioptric camera,planar region,obstacle avoidance,motion estimation,uncalibrated omnidirectional camera,omnidirectional camera,nonlinear optimization problem,visual tracking,direct approach,calibration phase,robotics,nonlinear programming,nonlinear optimization,pixel,field of view,image sensors,calibration,visualization | Field of view,Obstacle avoidance,Omnidirectional camera,Computer vision,Image sensor,Computer science,Camera auto-calibration,Camera resectioning,Artificial intelligence,Motion estimation,Robot | Conference |
ISBN | Citations | PageRank |
978-1-4244-3804-4 | 4 | 0.45 |
References | Authors | |
11 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Salazar-Garibay, A. | 1 | 4 | 0.45 |
| Ezio Malis | 2 | 1322 | 80.65 |
| Christopher Mei | 3 | 534 | 25.90 |