We propose a strategy for improving camera location estimation in structure from motion. Our setting assumes highly corrupted pairwise directions (i.e., normalized relative location vectors), so there is a clear room for improving current state-of-the-art solutions for this problem. Our strategy identifies severely corrupted pairwise directions by using a geometric consistency condition. It then selects a cleaner set of pairwise directions as a preprocessing step for common solvers. We theoretically guarantee the successful performance of a basic version of our strategy under a synthetic corruption model. Numerical results on artificial and real data demonstrate the significant improvement obtained by our strategy.
@article{arxiv.1804.02591,
title = {Estimation of Camera Locations in Highly Corrupted Scenarios: All About that Base, No Shape Trouble},
author = {Yunpeng Shi and Gilad Lerman},
journal= {arXiv preprint arXiv:1804.02591},
year = {2019}
}