期刊
JOURNAL OF MATHEMATICAL IMAGING AND VISION
卷 60, 期 4, 页码 609-632出版社
SPRINGER
DOI: 10.1007/s10851-017-0777-6
关键词
3D-reconstruction; Integration; Normal field; Gradient field; Variational methods; Photometric stereo; Shape-from-shading
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.
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