Abstract. We propose a sparsity-inducing multi-channel multiple region model for the efficient partitioning of a mesh into salient parts. Our approach is based on rewriting the Mumford-Shah models in terms of piece-wise smooth/constant functionals that incorporate a non-convex regularizer for minimizing the boundary lengths. The solution of this optimization problem, obtained by an efficient proximal forward backward algorithm, is used by a simple thresholding/clusterization procedure to segment the shape into the required number of parts. Therefore, it is not necessary to further solve the optimization problem for a different number of partitioning regions. Experimental results show the effectiveness and efficiency of our proposals when applied to both single- and multi-channel (shape characterizing) functions.

Huska, M., Morigi, S. (2017). Sparsity-inducing variational shape partitioning. ELECTRONIC TRANSACTIONS ON NUMERICAL ANALYSIS, 46, 36-54.

Sparsity-inducing variational shape partitioning

HUSKA, MARTIN;MORIGI, SERENA
2017

Abstract

Abstract. We propose a sparsity-inducing multi-channel multiple region model for the efficient partitioning of a mesh into salient parts. Our approach is based on rewriting the Mumford-Shah models in terms of piece-wise smooth/constant functionals that incorporate a non-convex regularizer for minimizing the boundary lengths. The solution of this optimization problem, obtained by an efficient proximal forward backward algorithm, is used by a simple thresholding/clusterization procedure to segment the shape into the required number of parts. Therefore, it is not necessary to further solve the optimization problem for a different number of partitioning regions. Experimental results show the effectiveness and efficiency of our proposals when applied to both single- and multi-channel (shape characterizing) functions.
2017
Huska, M., Morigi, S. (2017). Sparsity-inducing variational shape partitioning. ELECTRONIC TRANSACTIONS ON NUMERICAL ANALYSIS, 46, 36-54.
Huska, Martin ; Morigi, Serena
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/589683
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