Estimation of Camera Locations in Highly Corrupted Scenarios:
All About that Base, No Shape Trouble
Abstract
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-ofthe-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.