Pseudoconvex proximal splitting for L∞problems in multiview geometry
Eriksson,A and Isaksson,M 2014, Pseudoconvex proximal splitting for L∞problems in multiview geometry, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE Computer Society, Washington, D.C., United States, pp. 4066-4073, doi: 10.1109/CVPR.2014.518.
IEEE Conference on Computer Vision and Pattern Recognition
Start page
4066
End page
4073
Total pages
8
Publisher
IEEE Computer Society
Place of publication
Washington, D.C., United States
Summary
In this paper we study optimization methods for minimizing large-scale pseudoconvex L∞problems in multiview geometry. We present a novel algorithm for solving this class of problem based on proximal splitting methods. We provide a brief derivation of the proposed method along with a general convergence analysis. The resulting meta-algorithm requires very little effort in terms of implementation and instead makes use of existing advanced solvers for non-linear optimization. Preliminary experiments on a number of real image datasets indicate that the proposed method experimentally matches or outperforms current state-of-the-art solvers for this class of problems.
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