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A unifying and rigorous Shape From Shading method adapted to realistic data and applications

机译:适用于实际数据和应用程序的统一且严格的“ Shading From Shading”方法

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We propose a new method for the Lambertian Shape From Shading (SFS) problem based on the notion of Crandall-Lions viscosity solution. This method has the advantage of requiring the knowledge of the solution (the surface to be reconstructed) only on some part of the boundary and/or of the singular set (the set of the points at maximal intensity). Moreover it unifies in an unique mathematical formulation the works of Rouy et al. [34, 50], Falcone et al. [21], Prados et al. [46, 48, 49], based on the notion of viscosity solutions and the work of Dupuis and Oliensis [17] dealing with classical solutions and value functions. Also, it allows to generalize their results to the "perspective SFS" problem recently simultaneously introduced in [13,46,55]. While the theoretical part has been developed in [44], in this paper we give some stability results and we describe numerical schemes for the SFS based on this method. We construct provably convergent and robust algorithms. Finally, we apply our SFS method to real images and we suggest some real-life applications.
机译:我们基于Crandall-Lions粘性解决方案的概念,提出了一种针对Lambertian阴影着色(SFS)问题的新方法。该方法的优点是仅需要边界和/或奇异集合(最大强度的点集合)的某些部分的解(要重建的表面)知识。此外,它以独特的数学公式统一了Rouy等人的著作。 [34,50],Falcone等。 [21],普拉多斯等。 [46,48,49],基于粘性解的概念以及Dupuis和Oliensis [17]处理经典解和值函数的工作。同样,它允许将其结果推广到最近在[13,46,55]中同时引入的“透视SFS”问题。尽管在[44]中已经开发了理论部分,但在本文中,我们给出了一些稳定性结果,并基于此方法描述了SFS的数值方案。我们构造可证明的收敛性和鲁棒性算法。最后,我们将SFS方法应用于真实图像,并建议一些实际应用。

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