Fast Algorithms for L∞ Problems in Multiview Geometry
Abstract
Many problems in multi-view geometry, when posed as minimization of the maximum reprojection error across observations, can be solved optimally in polynomial time. We show that these problems are instances of a convex-concave generalized fractional program. We survey the major solution methods for solving problems of this form and present them in a unified framework centered around a single parametric optimization problem. We propose two new algorithms and show that the algorithm proposed by Olsson et al. [21] is a special case of a classical algorithm for generalized fractional programming. The performance of all the algorithms is compared on a variety of datasets, and the algorithm proposed by Gugat [12] stands out as a clear winner. An open source MATLAB toolbox that implements all the algorithms presented here is made available.
Cite
Text
Agarwal et al. "Fast Algorithms for L∞ Problems in Multiview Geometry." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2008. doi:10.1109/CVPR.2008.4587713Markdown
[Agarwal et al. "Fast Algorithms for L∞ Problems in Multiview Geometry." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2008.](https://mlanthology.org/cvpr/2008/agarwal2008cvpr-fast/) doi:10.1109/CVPR.2008.4587713BibTeX
@inproceedings{agarwal2008cvpr-fast,
title = {{Fast Algorithms for L∞ Problems in Multiview Geometry}},
author = {Agarwal, Sameer and Snavely, Noah and Seitz, Steven M.},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {2008},
doi = {10.1109/CVPR.2008.4587713},
url = {https://mlanthology.org/cvpr/2008/agarwal2008cvpr-fast/}
}