Pseudoconvex proximal splitting for L∞problems in multiview geometry
Contribuinte(s) |
[Unknown] |
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Data(s) |
01/01/2014
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Resumo |
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. |
Identificador | |
Idioma(s) |
eng |
Publicador |
IEEE Computer Society |
Relação |
http://dro.deakin.edu.au/eserv/DU:30069053/eriksson-pseudoconvexproximal-2014.pdf http://dro.deakin.edu.au/eserv/DU:30069053/evid-confcvprrvwgnrl-2014.pdf http://dro.deakin.edu.au/eserv/DU:30069053/isaksson-pseudoconvex-post-2014.pdf http://dro.deakin.edu.au/eserv/DU:30069053/t120723-eriksson-pseudoconvexproximal-20.pdf http://www.dx.doi.org/10.1109/CVPR.2014.518 |
Direitos |
2014, IEEE Computer Society |
Tipo |
Conference Paper |