1 November 2009 Fast viscosity solutions for shape from shading under a more realistic imaging model
Guohui Wang, Jiuqiang Han, Honghai Jia, Xinman Zhang
Author Affiliations +
Abstract
Shape from shading (SFS) has been a classical and important problem in the domain of computer vision. The goal of SFS is to reconstruct the 3-D shape of an object from its 2-D intensity image. To this end, an image irradiance equation describing the relation between the shape of a surface and its corresponding brightness variations is used. Then it is derived as an explicit partial differential equation (PDE). Using the nonlinear programming principle, we propose a detailed solution to Prados and Faugeras's implicit scheme for approximating the viscosity solution of the resulting PDE. Furthermore, by combining implicit and semi-implicit schemes, a new approximation scheme is presented. In order to accelerate the convergence speed, we adopt the Gauss-Seidel idea and alternating sweeping strategy to the approximation schemes. Experimental results on both synthetic and real images are performed to demonstrate that the proposed methods are fast and accurate.
©(2009) Society of Photo-Optical Instrumentation Engineers (SPIE)
Guohui Wang, Jiuqiang Han, Honghai Jia, and Xinman Zhang "Fast viscosity solutions for shape from shading under a more realistic imaging model," Optical Engineering 48(11), 117201 (1 November 2009). https://doi.org/10.1117/1.3257283
Published: 1 November 2009
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
Cameras

Optical engineering

Computer programming

Light sources

Surface plasmons

Optical spheres

3D image reconstruction

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