Accurate computation of single scattering in participating media with refractive boundaries

International audienceVolume caustics are high-frequency effects appearing in participating media with low opacity, when refractive interfaces are focusing the light rays. Refractions make them hard to compute, since screen locality does not correlate with spatial locality in the medium. In this paper we give a new method for accurate computation of single scattering effects in a participating media enclosed by refractive interfaces. Our algorithm is based on the observation that although radiance along each camera ray is irregular, contributions from individual triangles are smooth. Our method gives more accurate results than existing methods, faster. It uses minimal information and requires no precomputation or additional data structures

Capturing Spatially Varying Anisotropic Reflectance Parameters using Fourier Analysis

International audienceReflectance parameters condition the appearance of objects in photorealistic rendering. Practical acquisition of reflectance parameters is still a difficult problem. Even more so for spatially varying or anisotropic materials, which increase the number of samples required. In this paper, we present an algorithm for acquisition of spatially varying anisotropic materials, sampling only a small number of directions. Our algorithm uses Fourier analysis to extract the material parameters from a sub-sampled signal. We are able to extract diffuse and specular reflectance, direction of anisotropy, surface normal and reflectance parameters from as little as 20 sample directions. Our system makes no assumption about the stationarity or regularity of the materials, and can recover anisotropic effects at the pixel level

Multiscale feature-preserving smoothing of tomographic data

PosterInternational audienceComputer tomography (CT) has wide application in medical imaging and reverse engineering. Due to the limited number of projections used in reconstructing the volume, the resulting 3D data is typically noisy. Contouring such data, for surface extraction, yields surfaces with localised artifacts of complex topology. To avoid such artifacts, we propose a method for feature-preserving smoothing of CT data. The smoothing is based on anisotropic diffusion, with a diffusion tensor designed to smooth noise up to a given scale, while preserving features. We compute these diffusion kernels from the directional histograms of gradients around each voxel, using a fast GPU implementation

Point-Based Rendering for Homogeneous Participating Media with Refractive Boundaries

International audienceIllumination effects in translucent materials are a combination of several physical phenomena: refraction at the surface, absorption and scattering inside the material. Because refraction can focus light deep inside the material, where it will be scattered, practical illumination simulation inside translucent materials is difficult. In this paper, we present an a Point-Based Global Illumination method for light transport on homogeneous translucent materials with refractive boundaries. We start by placing light samples inside the translucent material and organizing them into a spatial hierarchy. At rendering, we gather light from these samples for each camera ray. We compute separately the sample contributions for single, double and multiple scattering, and add them. We present two implementations of our algorithm: an offline version for high-quality rendering and an interactive GPU implementation. The offline version provides significant speed-ups and reduced memory footprints compared to state-of-the-art algorithms, with no visible impact on quality. The GPU version yields interactive frame rates: 30 fps when moving the viewpoint, 25 fps when editing the light position or the material parameters

Multi-scale Feature-Preserving Smoothing of Images and Volumes on GPU

Les images et données volumiques sont devenues importantes dans notre vie quotidienne que ce soit sur le plan artistique, culturel, ou scientifique. Les données volumiques ont un intérêt important dans l'imagerie médicale, l'ingénierie, et l'analyse du patrimoine culturel. Ils sont créées en utilisant la reconstruction tomographique, une technique qui combine une large série de scans 2D capturés de plusieur points de vue. Chaque scan 2D est obtenu par des methodes de rayonnement : Rayons X pour les scanners CT, ondes radiofréquences pour les IRM, annihilation électron-positron pour les PET scans, etc. L'acquisition des images et données volumique est influencée par le bruit provoqué par différents facteurs. Le bruit dans les images peut être causée par un manque d'éclairage, des défauts électroniques, faible dose de rayonnement, et un mauvais positionnement de l'outil ou de l'objet. Le bruit dans les données volumique peut aussi provenir d'une variété de sources : le nombre limité de points de vue, le manque de sensibilité dans les capteurs, des contrastes élevé, les algorithmes de reconstruction employés, etc. L'acquisition de données non bruitée est iréalisable. Alors, il est souhaitable de réduire ou d'éliminer le bruit le plus tôt possible dans le pipeline. La suppression du bruit tout en préservant les caractéristiques fortes d'une image ou d'un objet volumique reste une tâche difficile. Nous proposons une méthode multi-échelle pour lisser des images 2D et des données tomographiques 3D tout en préservant les caractéristiques à l'échelle spécifiée. Notre algorithme est contrôlé par un seul paramètre la taille des caractéristiques qui doivent être préservées. Toute variation qui est plus petite que l'échelle spécifiée est traitée comme bruit et lissée, tandis que les discontinuités telles que des coins, des bords et des détails à plus grande échelle sont conservés. Nous démontrons les données lissées produites par notre algorithme permettent d'obtenir des images nettes et des iso-surfaces plus propres. Nous comparons nos résultats avec ceux des methodes précédentes. Notre méthode est inspirée par la diffusion anisotrope. Nous calculons nos tenseurs de diffusion à partir des histogrammes continues locaux de gradients autour de chaque pixel dans les images et autour de chaque voxel dans des volumes. Comme notre méthode de lissage fonctionne entièrement sur GPU, il est extrêmement rapide.Two-dimensional images and three-dimensional volumes have become a staple ingredient of our artistic, cultural, and scientific appetite. Images capture and immortalize an instance such as natural scenes, through a photograph camera. Moreover, they can capture details inside biological subjects through the use of CT (computer tomography) scans, X-Rays, ultrasound, etc. Three-dimensional volumes of objects are also of high interest in medical imaging, engineering, and analyzing cultural heritage. They are produced using tomographic reconstruction, a technique that combine a large series of 2D scans captured from multiple views. Typically, penetrative radiation is used to obtain each 2D scan: X-Rays for CT scans, radio-frequency waves for MRI (magnetic resonance imaging), electron-positron annihilation for PET scans, etc. Unfortunately, their acquisition is influenced by noise caused by different factors. Noise in two-dimensional images could be caused by low-light illumination, electronic defects, low-dose of radiation, and a mispositioning tool or object. Noise in three-dimensional volumes also come from a variety of sources: the limited number of views, lack of captor sensitivity, high contrasts, the reconstruction algorithms, etc. The constraint that data acquisition be noiseless is unrealistic. It is desirable to reduce, or eliminate, noise at the earliest stage in the application. However, removing noise while preserving the sharp features of an image or volume object remains a challenging task. We propose a multi-scale method to smooth 2D images and 3D tomographic data while preserving features at a specified scale. Our algorithm is controlled using a single user parameter the minimum scale of features to be preserved. Any variation that is smaller than the specified scale is treated as noise and smoothed, while discontinuities such as corners, edges and detail at a larger scale are preserved. We demonstrate that our smoothed data produces clean images and clean contour surfaces of volumes using standard surface-extraction algorithms. In addition to, we compare our results with results of previous approaches. Our method is inspired by anisotropic diffusion. We compute our diffusion tensors from the local continuous histograms of gradients around each pixel in imageSAVOIE-SCD - Bib.électronique (730659901) / SudocGRENOBLE1/INP-Bib.électronique (384210012) / SudocGRENOBLE2/3-Bib.électronique (384219901) / SudocSudocFranceF

Un modèle de BRDF bi-échelle combinant : Diffraction et Micro-facettes

National audienceWe present a Two-Scale BRDF model combining Microfacet and Diffraction theories. This new model explains better the different BRDF measurements compared to previous approaches

Création de storyboards dynamiques pour la visualisation d'animations

National audienceReprésenter un ensemble complexe de mouvements sous forme condensée, par exemple dans une image, est un problème qui se pose dans de nombreux domaines, allant de la visualisation scientifique à la conception de story-boards ou de bandes dessinées. Une image (espace à deux dimensions) ne peut représenter le mouvement de particules dans l'espace (données 4D) sans perte d'information. Pour compenser cette perte, plusieurs techniques ont été développées, allant de l'ajout d'indices visuels dans une image au découpage du mouvement en une séquence de plusieurs images. Dans cet article, nous présentons un pipeline pour générer, à partir de données correspondant à un ensemble de mouvements dans l'espace et sur une certaine durée temporelle, un storyboard résumant de manière compréhensible et efficace l'ensemble de l'animation. Notre méthode consiste à grouper les données ayant un mouvement similaire, puis à segmenter ces groupes pour isoler des positions clefs. Enfin, nous effectuons un rendu stylisé de la trajectoire correspondant à chaque segment. L'objectif de notre travail est de permettre une exploration dynamique du storyboard obtenu, de telle sorte qu'un utilisateur puisse observer les données à plusieurs échelles, aussi bien spatiales que temporelles. Voir aussi http://artis.imag.fr/Publications/2008/SH0

Combining Higher-Order Wavelets and Discontinuity Meshing: a Compact Representation for Radiosity

Colloque avec actes et comité de lecture. internationale.International audienceThe radiosity method is used for global illumination simulation in diffuse scenes, or as an intermediate step in other methods. Radiosity computations using Higher-Order wavelets achieve a compact representation of the illumination on many parts of the scene, but are more expensive near discontinuities, such as shadow boundaries. Other methods use a mesh, based on the set of discontinuities of the illumination function. The complexity of this set of discontinuities has so far proven prohibitive for large scenes, mostly because of the difficulty to robustly manage a geometrically complex set of triangles. In this paper, we present a method for computing radiosity that uses higher-order wavelet functions as a basis, and introduces discontinuities only when they simplify the resulting mesh. The result is displayed directly, without post-processing

Using Graphics Hardware to Speed-up Visibility Queries

International audienceWe present a visibility method that takes advantage of the graphics hardware to give fast answers to visibility queries. Our visibility method is designed to solve two types of visibility queries: point-based visibility queries, where several visibility queries share the same origin, and plane- based visibility queries, where several visibility queries have their origins on the same plane. Both occur frequently in global illumination algorithms. Combining the speed given by graphics hardware with a software heuristic to avoid reliability problems, our visibility method is signicantly faster than ray-casting, and still gives the same results