Minimal Solutions to Relative Pose Estimation from Two Views Sharing a Common Direction with Unknown Focal Length
Abstract
We propose minimal solutions to relative pose estimation problem from two views sharing a common direction with unknown focal length. This is relevant for cameras equipped with an IMU (inertial measurement unit), e.g., smart phones, tablets. Similar to the 6-point algorithm for two cameras with unknown but equal focal lengths and 7-point algorithm for two cameras with different and unknown focal lengths, we derive new 4- and 5-point algorithms for these two cases, respectively. The proposed algorithms can cope with coplanar points, which is a degenerate configuration for these 6- and 7-point counterparts. We present a detailed analysis and comparisons with the state of the art. Experimental results on both synthetic data and real images from a smart phone demonstrate the usefulness of the proposed algorithms.
Cite
Text
Ding et al. "Minimal Solutions to Relative Pose Estimation from Two Views Sharing a Common Direction with Unknown Focal Length." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020. doi:10.1109/CVPR42600.2020.00707Markdown
[Ding et al. "Minimal Solutions to Relative Pose Estimation from Two Views Sharing a Common Direction with Unknown Focal Length." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020.](https://mlanthology.org/cvpr/2020/ding2020cvpr-minimal/) doi:10.1109/CVPR42600.2020.00707BibTeX
@inproceedings{ding2020cvpr-minimal,
title = {{Minimal Solutions to Relative Pose Estimation from Two Views Sharing a Common Direction with Unknown Focal Length}},
author = {Ding, Yaqing and Yang, Jian and Ponce, Jean and Kong, Hui},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {2020},
doi = {10.1109/CVPR42600.2020.00707},
url = {https://mlanthology.org/cvpr/2020/ding2020cvpr-minimal/}
}