A consensus-based framework for distributed Bundle Adjustment
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Date
2016
Authors
Eriksson, A.
Bastian, J.
Chin, T.
Isaksson, M.
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Conference paper
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Proceedings / CVPR, IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2016, vol.2016-December, pp.1754-1762
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Anders Eriksson, John Bastian, Tat-Jun Chin and Mats Isaksson
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2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016) (27 Jun 2016 - 30 Jun 2016 : Las Vegas, NV, USA)
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.
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© 2016 IEEE