Eriksson, A.Bastian, J.Chin, T.Isaksson, M.2017-10-162017-10-162016Proceedings / 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.1754-176297814673885111063-6919http://hdl.handle.net/2440/108602In 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.en© 2016 IEEEGeometry, cameras, signal processing algorithms, computers, optimization, complexity theory, image reconstructionConference paper003005638810.1109/CVPR.2016.1942-s2.0-84986330142270688