Polynomial Methods for Structure from Motion
Abstract
There have been many attempts to solve the SFM problem, yet few practical solutions. Previous work has used either linearizations that ignore vital constraints or non-linear equations with multiple solutions, where the existence of multiple solutions has been ignored. First, we classify and analyze many existing methods and find that they do not work well in the presence of noise, or without a good initial estimate. Then, we propose new polynomial systems solutions for both orthographic and perspective projection that work better than existing methods in the presence of noise. Finally, we examine the effect of such factors as the number of frames and the axis and angle of rotation on the ability to recover structure. We found that additional frames are of no value and that large amounts of rotation resulting in disparate views are very helpful for accurate structure recovery.
Cite
Text
Jerian and Jain. "Polynomial Methods for Structure from Motion." IEEE/CVF International Conference on Computer Vision, 1988. doi:10.1109/CCV.1988.589991Markdown
[Jerian and Jain. "Polynomial Methods for Structure from Motion." IEEE/CVF International Conference on Computer Vision, 1988.](https://mlanthology.org/iccv/1988/jerian1988iccv-polynomial/) doi:10.1109/CCV.1988.589991BibTeX
@inproceedings{jerian1988iccv-polynomial,
title = {{Polynomial Methods for Structure from Motion}},
author = {Jerian, Charles and Jain, Ramesh C.},
booktitle = {IEEE/CVF International Conference on Computer Vision},
year = {1988},
pages = {197-206},
doi = {10.1109/CCV.1988.589991},
url = {https://mlanthology.org/iccv/1988/jerian1988iccv-polynomial/}
}