Pseudoconvex Proximal Splitting for L-infinity Problems in Multiview Geometry
作者： Anders Eriksson , Mats Isaksson
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摘要: In this paper we study optimization methods for minimizing large-scale pseudoconvex ∞ problems in multiview geometry. We present a novel algorithm solving class of problem based on proximal splitting methods. provide brief derivation the proposed method along with general convergence analysis. The resulting meta-algorithm requires very little effort terms implementation and instead makes use existing advanced solvers non-linear optimization. Preliminary experiments number real image datasets indicate that experimentally matches or outperforms current state-of-the-art problems.
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