Name
Abstract | ||
|---|---|---|
This paper presents a novel approach for the extrinsic parameter estimation of omnidirectional cameras with respect to a 3D Lidar coordinate frame. The method works without specific setup and calibration targets, using only a pair of 2D-3D data. Pose estimation is formulated as a 2D-3D nonlinear shape registration task which is solved without point correspondences or complex similarity metrics. It relies on a set of corresponding regions, and pose parameters are obtained by solving a small system of nonlinear equations. The efficiency and robustness of the proposed method was confirmed on both synthetic and real data in urban environment. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-319-16181-5_49 | COMPUTER VISION - ECCV 2014 WORKSHOPS, PT II |
Keywords | Field | DocType |
Omnidirectional camera, Lidar, Pose estimation, Fusion | Omnidirectional camera,Omnidirectional antenna,Computer vision,Nonlinear system,Computer science,Pose,Robustness (computer science),Lidar,Artificial intelligence,Estimation theory,Calibration | Conference |
Volume | ISSN | Citations |
8926 | 0302-9743 | 4 |
PageRank | References | Authors |
0.47 | 21 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Levente Tamas | 1 | 25 | 7.52 |
| Robert Frohlich | 2 | 8 | 1.56 |
| Zoltan Kato | 3 | 265 | 28.28 |