Viewing Graph Solvability in Practice
Abstract
We present an advance in understanding the projective Structure-from-Motion, focusing in particular on the viewing graph: such a graph has cameras as nodes and fundamental matrices as edges. We propose a practical method for testing finite solvability, i.e., whether a viewing graph induces a finite number of camera configurations. Our formulation uses a significantly smaller number of equations (up to 400x) with respect to previous work. As a result, this is the only method in the literature that can be applied to large viewing graphs coming from real datasets, comprising up to 300K edges. In addition, we develop the first algorithm for identifying maximal finite-solvable components.
Cite
Text
Arrigoni et al. "Viewing Graph Solvability in Practice." International Conference on Computer Vision, 2023. doi:10.1109/ICCV51070.2023.00748Markdown
[Arrigoni et al. "Viewing Graph Solvability in Practice." International Conference on Computer Vision, 2023.](https://mlanthology.org/iccv/2023/arrigoni2023iccv-viewing/) doi:10.1109/ICCV51070.2023.00748BibTeX
@inproceedings{arrigoni2023iccv-viewing,
title = {{Viewing Graph Solvability in Practice}},
author = {Arrigoni, Federica and Pajdla, Tomas and Fusiello, Andrea},
booktitle = {International Conference on Computer Vision},
year = {2023},
pages = {8147-8155},
doi = {10.1109/ICCV51070.2023.00748},
url = {https://mlanthology.org/iccv/2023/arrigoni2023iccv-viewing/}
}