Name
Title | ||
|---|---|---|
Pose estimation from uncertain omnidirectional image data using line-plane correspondences |
Abstract | ||
|---|---|---|
Omnidirectional vision is highly beneficial for robot navigation. We present a novel perspective pose estimation for omnidirectional vision involving a parabolic central catadioptric sensor using line-plane correspondences. We incorporate an appropriate and approved stochastic method to deal with uncertainties in the data. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11861898_59 | DAGM-Symposium |
Keywords | Field | DocType |
uncertain omnidirectional image data,omnidirectional vision,stochastic method,robot navigation,novel perspective,line-plane correspondence,parabolic central catadioptric sensor,pose estimation | Computer vision,Omnidirectional antenna,Computer science,Pose,Catadioptric sensor,Panoramic photography,Artificial intelligence,Robot,Robotics,Focus (optics),Parabola | Conference |
Volume | ISSN | ISBN |
4174 | 0302-9743 | 3-540-44412-2 |
Citations | PageRank | References |
0 | 0.34 | 8 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Christian Gebken | 1 | 11 | 2.16 |
| Antti Tolvanen | 2 | 4 | 1.12 |
| Gerald Sommer | 3 | 0 | 0.34 |