Estimation of illuminant direction, albedo, and shape from shading

Zheng, Qinfen; Chellappa, Rama

doi:10.1109/34.85658

Cited by 350 publications

(165 citation statements)

References 17 publications

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“…From a mathematical point of view, this coincides the requirement that, for any point of the reconstruction domain, the surface height is (or needs to be) independent from the path of integration (Frankot and Chellappa, 1988;Horn, 1989;Zheng and Chellappa, 1991). Considering that, it is possible to formulate a relation between normal N and surface gradient ∇ Z as follows:…”

Section: Functional Contributionsmentioning

confidence: 99%

Two Simple Yet Effective Strategies for Avoiding Over-Smoothing in SFS Problem

Carfagni¹,

Furferi²,

Governi³

et al. 2016

Journal of Computer Science

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Minimization techniques are widely used for retrieving a 3D surface starting from a single shaded image i.e., for solving the shape from shading problem. Such techniques are based on the assumption that expected surface to be retrieved coincides with the one that minimize a properly developed functional, consisting of several contributions. Among the possible contributes defining the functional, the so called "smoothness constraint" is always used since it guides the convergence of the minimization process towards a more accurate solution. Unfortunately, in areas where actually brightness changes rapidly, it also introduces an undesired over-smoothing effect. The present work proposes two simple yet effective strategies for avoiding the typical over-smoothing effect, with regards to the image regions in which this effect is particularly undesired (e.g., areas where surface details are to be preserved in the reconstruction). Tested against a set of case studies the strategies prove to outperform traditional SFS-based methods.

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Section: Functional Contributionsmentioning

confidence: 99%

Two Simple Yet Effective Strategies for Avoiding Over-Smoothing in SFS Problem

Carfagni¹,

Furferi²,

Governi³

et al. 2016

Journal of Computer Science

View full text Add to dashboard Cite

show abstract

“…According to the differences of the additional constraints, SFS techniques can be divided into four groups: minimization approaches, propagation approaches, local approaches, and linear approaches [6]. The paper mainly introduces Zheng's [7] algorithm, which is a minimization approach.…”

Section: Sfs Algorithmmentioning

confidence: 99%

“…Zheng [7] computed the solution by minimizing an energy function over the entire image. The function involves a brightness constraint, an integrability constraint, and an intensity gradient constraint.…”

Section: Algorithmmentioning

confidence: 99%

“…In variational calculus, the Euler equations, which are differential equations, are first computed and then solved discretely to minimize the energy function. Zheng [7] simplified the Euler equations by taking the first-order Taylor series of the reflectance map and representing the depth, gradient, and their derivatives in discrete form. Then, a new iterative scheme was derived, which updates depth and gradients simultaneously.…”

Section: Algorithmmentioning

confidence: 99%

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Inspection of weld shape based on the shape from shading

Quan-ying

Chen

Lin

2005

Int J Adv Manuf Technol

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The weld bead shape is crucial for weld quality. Automatic inspection on the 3D shape of a weld bead is achieved by recording the image of the weld bead with an optical sensing method and then calculating the 3D shape parameters with a shape-from-shading technology based on a single image in the computer-vision domain. The paper first introduces a method of shape from shading based on a single image and puts forward its implementation. It then presents the improved measures of the original algorithm according to the defects of the computed results and finds accuracy compared with the former method by a synthetic image. Finally, the improved algorithm is applied to the surface height reconstruction of weld bead successfully.

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“…For example, segmentation algorithms can be improved if the incoming light direction is known (Powel et al, 2001). Moreover, shape from shading approaches rely on some information concerning light sources (Zheng and Chellappa, 1991;Lee and Rosenfeld, 1985;Brooks and Horn, 1985), as well as augmented reality where virtual objects have to be lit with real light sources. Today applications in computer graphics are more and more concerned with this topic, especially with image-based rendering approaches.…”

Section: Introductionmentioning

confidence: 99%

A Framework for Automatically Recovering Object Shape, Reflectance and Light Sources from Calibrated Images

Mercier

Méneveaux

Fournier

2006

Int J Comput Vision

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In this paper, we present a complete framework for recovering an object shape, estimating its reflectance properties and light sources from a set of images. The whole process is performed automatically. We use the shape from silhouette approach proposed by R. Szeliski (1993) combined with image pixels for reconstructing a triangular mesh according to the marching cubes algorithm. A classification process identifies regions of the object having the same appearance. For each region, a single point or directional light source is detected. Therefore, we use specular lobes, lambertian regions of the surface or specular highlights seen on images. An identification method jointly (i) decides what light sources are actually significant and (ii) estimates diffuse and specular coefficients for a surface represented by the modified Phong model (Lewis, 1994). In order to validate our algorithm efficiency, we present a case study with various objects, light sources and surface properties. As shown in the results, our system proves accurate even for real objects images obtained with an inexpensive acquisition system.

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Estimation of illuminant direction, albedo, and shape from shading

Cited by 350 publications

References 17 publications

Two Simple Yet Effective Strategies for Avoiding Over-Smoothing in SFS Problem

Two Simple Yet Effective Strategies for Avoiding Over-Smoothing in SFS Problem

Inspection of weld shape based on the shape from shading

A Framework for Automatically Recovering Object Shape, Reflectance and Light Sources from Calibrated Images

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