Variational Methods for Normal Integration

Abstract : 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, pho-tometric stereo, deflectometry, etc. 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.
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Contributeur : Yvain Quéau <>
Soumis le : lundi 18 septembre 2017 - 15:10:45
Dernière modification le : mercredi 27 février 2019 - 10:04:05


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  • HAL Id : hal-01334351, version 3



Yvain Quéau, Jean-Denis Durou, Jean-François Aujol. Variational Methods for Normal Integration. 2016. 〈hal-01334351v3〉



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