Exact Camera Location Recovery By Least Unsquared Deviations
Keywords
Camera location estimation; Convex recovery; Least unsquared deviations; Random graph theory; Robust estimation; Structure from motion
Abstract
We establish exact recovery for the Least Unsquared Deviations (LUD) algorithm of Ozye sil 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 for camera locations was established for the ShapeFit algorithm by Hand, Lee, and Voroninski, but with typically less corruption.
Publication Date
1-1-2018
Publication Title
SIAM Journal on Imaging Sciences
Volume
11
Issue
4
Number of Pages
2692-2721
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1137/17M115061X
Copyright Status
Unknown
Socpus ID
85064212658 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85064212658
STARS Citation
Lerman, Gilad; Shi, Yunpeng; and Zhang, Teng, "Exact Camera Location Recovery By Least Unsquared Deviations" (2018). Scopus Export 2015-2019. 9268.
https://stars.library.ucf.edu/scopus2015/9268