# Exact Camera Location Recovery by Least Unsquared Deviations

arXiv: https://arxiv.org/abs/1709.09683 · HTML: https://mlsanity.com/paper/1709.09683/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Sep 2017.

## Built on by (most cited first, 3 of 3)

- [Cycle-Sync: Robust Global Camera Pose Estimation through Enhanced Cycle-Consistent Synchronization](https://mlsanity.com/paper/2511.02329/) (2025)
- [TriDE: Triangle-Consistent Translation Directions for Global Camera Pose Estimation](https://mlsanity.com/paper/2605.06889/) (2026)
- [TriP: A Triangle Puzzle Approach to Robust Translation Averaging](https://mlsanity.com/paper/2605.07143/) (2026)

## Abstract (arXiv)

We establish exact recovery for the Least Unsquared Deviations (LUD) algorithm of Ozyesil and Singer. More precisely, we show that for sufficiently many cameras with given corrupted pairwise directions, where both camera locations and pairwise directions are generated by a special probabilistic model, the LUD algorithm exactly recovers the camera locations with high probability. A similar exact recovery guarantee was established for the ShapeFit algorithm by Hand, Lee and Voroninski, but with typically less corruption.