A spherical eye from multiple cameras (makes better models of the world)
| Title | A spherical eye from multiple cameras (makes better models of the world) |
| Publication Type | Conference Papers |
| Year of Publication | 2001 |
| Authors | Baker P, Fermüller C, Aloimonos Y, Pless R |
| Conference Name | Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2001. CVPR 2001 |
| Date Published | 2001/// |
| Publisher | IEEE |
| ISBN Number | 0-7695-1272-0 |
| Keywords | 3D motion estimation, Calibration, camera network, CAMERAS, Computer vision, egomotion recovery, geometric configuration, geometric constraint, image gradients, image sampling, imaging system, Laboratories, Layout, Motion estimation, multiple cameras, Pixel, Robot vision systems, SHAPE, shape models, Space technology, spherical eye, system calibration, video, video cameras, video signal processing, visual sphere sampling |
| Abstract | The paper describes an imaging system that has been designed specifically for the purpose of recovering egomotion and structure from video. The system consists of six cameras in a network arranged so that they sample different parts of the visual sphere. This geometric configuration has provable advantages compared to small field of view cameras for the estimation of the system's own motion and consequently the estimation of shape models from the individual cameras. The reason is that inherent ambiguities of confusion between translation and rotation disappear. We provide algorithms for the calibration of the system and 3D motion estimation. The calibration is based on a new geometric constraint that relates the images of lines parallel in space to the rotation between the cameras. The 3D motion estimation uses a constraint relating structure directly to image gradients. |
| DOI | 10.1109/CVPR.2001.990525 |