Name
Abstract | ||
|---|---|---|
This paper presents a direct and stochastic technique for real time estimation of on board camera position and orientation--the ego-motion problem. An on board stereo vision system is used. Unlike existing works, which rely on feature extraction either in the image domain or in 3D space, our proposed approach directly estimates the unknown parameters from the brightness of a stream of stereo pairs. The pose parameters are tracked using the particle filtering framework which implicitly enforces the smoothness constraints on the dynamics. The proposed technique can be used in driving assistance applications as well as in augmented reality applications. Experimental results and comparisons on urban environments with different road geometries are presented. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-74260-9_42 | ICIAR |
Keywords | Field | DocType |
board stereo vision system,proposed technique,stereo pair,real-time vehicle ego-motion,particle filter,assistance application,ego-motion problem,augmented reality application,board camera position,different road geometries,stochastic technique,augmented reality,feature extraction,real time,stereo vision | Stereo cameras,Computer vision,Computer graphics (images),Computer science,Stereopsis,Particle filter,Feature extraction,Augmented reality,Artificial intelligence,Smoothness,Brightness,Computer stereo vision | Conference |
Volume | ISSN | ISBN |
4633 | 0302-9743 | 3-540-74258-1 |
Citations | PageRank | References |
1 | 0.34 | 4 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fadi Dornaika | 1 | 809 | 96.43 |
| Angel Domingo Sappa | 2 | 565 | 33.54 |