QUÉAU, Yvain; DUROU, Jean-Denis; AUJOL, Jean-François

doi:10.1007/s10851-017-0777-6

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QUÉAU, Yvain
Technische Universität Munchen - Technical University Munich - Université Technique de Munich [TUM]

DUROU, Jean-Denis
Real Expression Artificial Life [IRIT-REVA]

AUJOL, Jean-François
Institut de Mathématiques de Bordeaux [IMB]
Institut universitaire de France [IUF]

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Journal of Mathematical Imaging and Vision. 2018-05, vol. 60, n° 4, p. 609-632

Springer Verlag

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The need for an efficient method of integration of a dense normal field is inspired by several computer vision tasks, such as shape-from-shading, photometric stereo, deflectometry. Inspired by edge-preserving methods from image processing, we study in this paper several variational approaches for normal integration, with a focus on non-rectangular domains, free boundary and depth discontinuities. We first introduce a new discretization for quadratic integration, which is designed to ensure both fast recovery and the ability to handle non-rectangular domains with a free boundary. Yet, with this solver, discontinuous surfaces can be handled only if the scene is first segmented into pieces without discontinuity. Hence, we then discuss several discontinuity-preserving strategies. Those inspired, respectively, by the Mumford-Shah segmentation method and by anisotropic diffusion, are shown to be the most effective for recovering discontinuities.< Réduire

Mots clés en anglais

integration

3D-reconstruction

normal field

gradient field

variational methods

photometric stereo

shape-from-shading

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Variational Methods for Normal Integration

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