A Consensus-Based Framework for Distributed Bundle Adjustment
Anders Eriksson, John Bastian, Tat-Jun Chin, Mats Isaksson
Abstract
In this paper we study large-scale optimization problems in multi-view geometry, in particular the Bundle Adjustment problem. In its conventional formulation, the complexity of existing solvers scale poorly with problem size, hence this component of the Structure-from-Motion pipeline can quickly become a bottle-neck. Here we present a novel formulation for solving bundle adjustment in a truly distributed manner using consensus based optimization methods. Our algorithm is presented with a concise derivation based on proximal splitting, along with a theoretical proof of convergence and brief discussions on complexity and implementation. Experiments on a number of real image datasets convincingly demonstrates the potential of the proposed method by outperforming the conventional bundle adjustment formulation by orders of magnitude.
BibTeX
@inproceedings{cvpr2016_aconsensusbasedf,
title = {A Consensus-Based Framework for Distributed Bundle Adjustment},
author = {Anders Eriksson and John Bastian and Tat-Jun Chin and Mats Isaksson},
booktitle = {CVPR 2016},
year = {2016}
}