2016
DOI: 10.1016/j.cviu.2015.11.019
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Height from photometric ratio with model-based light source selection

Abstract: In this paper, we present a photometric stereo algorithm for estimating surface height. We follow recent work that uses photometric ratios to obtain a linear formulation relating surface gradients and image intensity. Using smoothed finite difference approximations for the surface gradient, we are able to express surface height recovery as a linear least squares problem that is large but sparse. In order to make the method practically useful, we combine it with a model-based approach that excludes observations… Show more

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Cited by 28 publications
(30 citation statements)
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“…Wu et al [24] considered the 3D recovery problem using a convex optimization technique to separate specularities as deviations from the basic Lambertian assumption, defined in the objective function. Smith and Fang [25] used a model-based approach that excludes observations that do not fit the Lambertian image formation model. Hertzmann and Seitz [26] employed reference objects which are considered to be of homogeneous material for simplicity, meaning that purely specular or purely diffuse materials are addressed.…”
Section: Introductionmentioning
confidence: 99%
“…Wu et al [24] considered the 3D recovery problem using a convex optimization technique to separate specularities as deviations from the basic Lambertian assumption, defined in the objective function. Smith and Fang [25] used a model-based approach that excludes observations that do not fit the Lambertian image formation model. Hertzmann and Seitz [26] employed reference objects which are considered to be of homogeneous material for simplicity, meaning that purely specular or purely diffuse materials are addressed.…”
Section: Introductionmentioning
confidence: 99%
“…Recently, new PS models based on nonlinear PDEs have attracted increasing interest [9,10,36,39,40,50,54]. Recently, new PS models based on nonlinear PDEs have attracted increasing interest [9,10,36,39,40,50,54].…”
mentioning
confidence: 99%
“…Recently, new PS models based on nonlinear PDEs have attracted increasing interest [9,10,36,39,40,50,54]. However, such methods remain computationally very intensive: it is simpler to eliminate the nonlinearity, through image ratios, as done in [36,39,40,51,54]. This system of nonlinear PDEs can be solved using calculus of variations [50] or proximal methods [20].…”
mentioning
confidence: 99%
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