Robust Absolute and Relative Pose Estimation of a Central Camera System from 2D-3D Line Correspondences
Abstract
We propose a new algorithm for estimating the absolute and relative pose of a camera system composed of general central projection cameras such as perspective and omnidirectional cameras. First, we derive a minimal solver for the minimal case of 3 line pairs per camera, which is used within a RANSAC algorithm for outlier filtering. Second, we also formulate a direct least squares solver which finds an optimal solution in case of noisy (but inlier) 2D-3D line pairs. Both solver relies on Grobner basis, hence they provide an accurate solution within a few milliseconds in Matlab. The algorithm has been validated on a large synthetic dataset as well as real data. Experimental results confirm the stable and real-time performance under realistic outlier ratio and noise on the line parameters. Comparative tests show that our method compares favorably to the latest state of the art algorithms.
Cite
Text
Abdellali et al. "Robust Absolute and Relative Pose Estimation of a Central Camera System from 2D-3D Line Correspondences." IEEE/CVF International Conference on Computer Vision Workshops, 2019. doi:10.1109/ICCVW.2019.00118Markdown
[Abdellali et al. "Robust Absolute and Relative Pose Estimation of a Central Camera System from 2D-3D Line Correspondences." IEEE/CVF International Conference on Computer Vision Workshops, 2019.](https://mlanthology.org/iccvw/2019/abdellali2019iccvw-robust/) doi:10.1109/ICCVW.2019.00118BibTeX
@inproceedings{abdellali2019iccvw-robust,
title = {{Robust Absolute and Relative Pose Estimation of a Central Camera System from 2D-3D Line Correspondences}},
author = {Abdellali, Hichem and Frohlich, Robert and Kato, Zoltan},
booktitle = {IEEE/CVF International Conference on Computer Vision Workshops},
year = {2019},
pages = {895-904},
doi = {10.1109/ICCVW.2019.00118},
url = {https://mlanthology.org/iccvw/2019/abdellali2019iccvw-robust/}
}