Abstract
A parametric camera model and calibration procedures are developed for an outdoor active camera system with pan, tilt and zoom control. Unlike traditional methods, active camera motion plays a key role in the calibration process, and no special laboratory setups are required. Intrinsic parameters are estimated automatically by fitting parametric models to the optic flow induced by rotating and zooming. No knowledge of 3D scene structure is needed. Extrinsic parameters are calculated by actively rotating the camera to sight a sparse set of surveyed landmarks over a virtual hemispherical field of view, yielding a well-conditioned pose estimation problem.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 528-534 |
| Number of pages | 7 |
| Journal | Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition |
| Volume | 1 |
| State | Published - 1999 |
| Event | Proceedings of the 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'99) - Fort Collins, CO, USA Duration: Jun 23 1999 → Jun 25 1999 |
All Science Journal Classification (ASJC) codes
- Software
- Computer Vision and Pattern Recognition