Motion Estimation for Multi-Camera Systems Using Global Optimization
Abstract
We present a motion estimation algorithm for multi-camera systems consisting of more than one calibrated camera securely attached on a moving object. So, they move all together, but do not require to have overlapping views across the cameras. The geometrically optimal solution of the motion for the multi-camera systems under Linfin norm is provided in this paper using a global optimization technique which has been introduced recently in the computer vision research field. Taking advantage of an optimal estimate of the essential matrix through searching rotation space, we provide the optimal solution for translation by using linear programming and branch & bound algorithm. Synthetic and real data experiments are conducted, and they show more robust and improved performance than the previous methods.
Cite
Text
Kim et al. "Motion Estimation for Multi-Camera Systems Using Global Optimization." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2008. doi:10.1109/CVPR.2008.4587680Markdown
[Kim et al. "Motion Estimation for Multi-Camera Systems Using Global Optimization." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2008.](https://mlanthology.org/cvpr/2008/kim2008cvpr-motion/) doi:10.1109/CVPR.2008.4587680BibTeX
@inproceedings{kim2008cvpr-motion,
title = {{Motion Estimation for Multi-Camera Systems Using Global Optimization}},
author = {Kim, Jae-Hak and Li, Hongdong and Hartley, Richard I.},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {2008},
doi = {10.1109/CVPR.2008.4587680},
url = {https://mlanthology.org/cvpr/2008/kim2008cvpr-motion/}
}