Space and camera path reconstruction for omni-directional vision
| dc.creator | Knill, Oliver | |
| dc.creator | Ramirez-Herran, Jose | |
| dc.date | 2007-08-17 | |
| dc.date.accessioned | 2026-07-07T08:24:14Z | |
| dc.date.available | 2026-07-07T08:24:14Z | |
| dc.description | In this paper, we address the inverse problem of reconstructing a scene as well as the camera motion from the image sequence taken by an omni-directional camera. Our structure from motion results give sharp conditions under which the reconstruction is unique. For example, if there are three points in general position and three omni-directional cameras in general position, a unique reconstruction is possible up to a similarity. We then look at the reconstruction problem with m cameras and n points, where n and m can be large and the over-determined system is solved by least square methods. The reconstruction is robust and generalizes to the case of a dynamic environment where landmarks can move during the movie capture. Possible applications of the result are computer assisted scene reconstruction, 3D scanning, autonomous robot navigation, medical tomography and city reconstructions. | |
| dc.identifier | https://arxiv.org/abs/0708.2442 | |
| dc.identifier | http://arxiv.org/abs/0708.2442 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/136275 | |
| dc.subject | Computer Vision and Pattern Recognition | |
| dc.subject | Artificial Intelligence | |
| dc.title | Space and camera path reconstruction for omni-directional vision | |
| dc.type | text |