Abstract
Previous algorithms that recover camera motion from image velocities suffer from both bias and excessive variance in the results. We propose a robust estimator of camera motion that is statistically consistent when image noise is isotropic. Consistency means that the estimated motion converges in probability to the true value as the number of image points increases. An algorithm based on reweighted Gauss-Newton iterations handles 100 velocity measurements in about 50 milliseconds on a workstation.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 164-170 |
| Number of pages | 7 |
| Journal | Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition |
| Volume | 1 |
| State | Published - 1999 |
| Externally published | Yes |
| 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 |
ASJC Scopus subject areas
- Software
- Computer Vision and Pattern Recognition