1dsfm
Kyle Wilson and Noah Snavely

@inproceedings{wilson_eccv2014_1dsfm,
title= {1dsfm},
author= {Kyle Wilson and Noah Snavely},
booktitle= {Proceedings of the European Conference on Computer Vision ({ECCV})},
year= {2014},
abstract= {We present a simple, effective method for solving structure from motion problems by averaging epipolar geometries. Based on recent successes in solving for global camera rotations using averaging schemes, we focus on the problem of solving for 3D camera translations given a network of noisy pairwise camera translation directions (or 3D point observations). To do this well, we have two main insights. First, we propose a method for removing outliers from problem instances by solving simpler low-dimensional subproblems, which we refer to as 1DSfM problems. Second, we present a simple, principled averaging scheme. We demonstrate this new method in the wild on Internet photo collections. 

Dataset scraped 23 February 2019

Code and papers scraped 15 July 2022},
keywords= {Dataset, photos, structure from motion, landmark, cornell, photo, paper, code, photographs, sfm},
terms= {},
license= {},
superseded= {},
url= {https://research.cs.cornell.edu/1dsfm/}
}