Photometric reconstruction of a dynamic textured surface from just one color image acquisition

http://www.opticsinfobase.org/josaa/abstract.cfm?msid=85528 This article has been selected for inclusion in the Virtual Journal for Biomedical Optics (Vol. 3, Iss. 4)International audienceTextured surface analysis is essential for many applications. We present a three-dimensional recovery approach for real textured surfaces based on photometric stereo. The aim is to be able to measure the textured surfaces with a high degree of accuracy. For this, we use a color digital sensor and principles of color photometric stereo. This method uses a single color image, instead of a sequence of gray-scale images, to recover the surface of the three dimensions. It can thus be integrated into dynamic systems where there is significant relative motion between the object and the camera. To evaluate the performances of our method, we compare it on real textured surfaces to traditional photometric stereo using three images. We show thus that it is possible to have similar results with just one color image

Isotropic and Anisotropic Interfaced Lambertian Microfacets

Specular microfacet distributions have been successfully employed by many authors for representing materials glossiness, and they are generally combined with a Lambertian term that accounts for the colored aspect. Such a representation makes use of the Fresnel reflectance factor at the interface, but the transmission factor is often ignored. In addition, the generalization to microfacet distributions with a more general reflectance is known to be complex, since it requires to solve an angular integral that has no analytical solution. This paper proposes a complete framework for physically handling both reflection and transmission with microfacet distributions. First, we show how transmission affects reflectance of an interfaced Lambertian model, and provide an analytical description of an individual microfacet reflectance. Second, we describe a method for handling distributions of such microfacets in any physically based Monte-Carlo rendering systems. Our approach generalizes several previous models, including flat Lambertian materials as well as specular and Lambertian microfacets. The result section illustrates the wide range of materials that can be possibly taken into account with this representation

3D Extraction of the Relief of Road Surface through Image Analysis

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3D extraction of the relief of road surface through image analysis

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La BRDF et son utilisation en synthèse d’images

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Localization of free 3D surfaces by the mean of photometric stereovision

International audienceWithin the framework of the analysis of 3D textured surface through imageanalysis, we approach here the case of the 3D interfaces (fluid-solid) surfaces for the analysisof the local variations of their relief. Generally, the interaction between the light and these localvariations of the relief leads to a textured images of these surfaces. Our aim here is to achievethe feasibility of this measurement through a local relief extraction based on photometricstereovision. The proposed approach is an original adaptation stereovision based onphotometric model to the case of free surfaces with a high degree of variation and withLambertian photometric behaviour .The suggested method is presented and the relevance ofthis approach for that kind of surface is tested on particular shape. The results obtained are thefirst step of a global study of the displacement of the local variation of this 3D free surface

Accurate image quantization adapted to multisource photometric reconstruction for rough textured surface analysis

International audienceIn classical photometric stereo (PS), a Lambertian surface is illuminated from three distant light sources to recover one normal direction per pixel of the input image. In continuous noiseless cases, PS allows us to reconstruct the textured surfaces in three-dimensions with a high degree of accuracy and a high resolution. In the real world, an image is a digital quantization, a limited and noisy representation of a surface. In this paper, we present an accurate 3D recovery approach for real textured surfaces based on an acquisition PS method. The proposed method uses a sequence of images for each light source to recover an accurate and unlimited representation of a surface. To evaluate the performances of the proposed method, we compare it to other traditional PS methods on real textured surfaces

Métrologie optique rapide par projection de grilles pour le contrôle qualité du positionnement de rivets

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Stéréo-Photométrie itérative dans le cas de sources lumineuses ponctuelles non uniformes.

International audienceDans le domaine de la vison par ordinateur la reconstruction tridimensionnelle par stéréo-photométrie est répandue. Sa mise en oeuvre peut être effectuée à partir de matériel grand public et les résultats obtenus sont très précis pour des temps d'acquisition courts. Néanmoins la stéréo-photométrie est régie par des contraintes d'application telles que l'utilisation de sources lumineuses directionnelles et uniformes. Mais par souci de miniaturisation les sources utilisées sont généralement ponctuelles et les résultats de reconstruction sont fortement biaisés. Nous proposons une méthode rapide et robuste qui prend en compte les propriétés du système d'éclairage et la géométrie de la surface analysée pour se placer dans les conditions optimales d'utilisation de la stéréo-photométrie

Tridimensional Reconstruction by Photometric Stereo with Near Spot Light Sources

International audienceIn this paper, we propose a method for taking into account lighting conditions for photometric stereo. Indeed, with its classic form, the photometric stereo requires directional light sources and uniform intensity to determine the geometry and albedo of a surface from a reverse illumination model. These constraints are usually not realistic in practice for compact systems, our formulation thus takes account all lighting system properties. We use an iterative process to include the geometry of the surface in the reverse illumination model. Each iteration provides a refined reconstruction and significantly improves the results. Our method does not require a new illumination models and the iteration number is small. It allows to quickly recover geometry and albedo. To evaluate the performance of our method, we compare it to classical photometric stereo by simulation and on real surfaces