Sparse BRDF Approximation using Compressive Sensing

International audienceWe experiment a BRDF acquisiton method from a single picture, knowing geometry and illumination. To tackle such a severely underconstrained problem, we express the BRDF in a high dimensional basis, and perform the reconstruction using compressive sensing, looking for the most sparse solution to the linear problem of fitting the measurement image.Nous expérimentons une méthode d'acquisition de BRDF à partir d'une image. Nous exprimons la BRDF dans une base de grande dimension et reconstruisons la brdf à l'aide du compressive sensing

Sparse BRDF Approximation using Compressive Sensing

International audienceWe experiment a BRDF acquisiton method from a single picture, knowing geometry and illumination. To tackle such a severely underconstrained problem, we express the BRDF in a high dimensional basis, and perform the reconstruction using compressive sensing, looking for the most sparse solution to the linear problem of fitting the measurement image.Nous expérimentons une méthode d'acquisition de BRDF à partir d'une image. Nous exprimons la BRDF dans une base de grande dimension et reconstruisons la brdf à l'aide du compressive sensing

Accurate and Efficient Filtering using Anisotropic Filter Decomposition

Efficient filtering remains an important challenge in computer graphics, particularly when filters are spatially-varying, have large extent, and/or exhibit complex anisotropic profiles. We present an efficient filtering approach for these difficult cases based on anisotropic filter decomposition (IFD). By decomposing complex filters into linear combinations of simpler, displaced isotropic kernels, and precomputing a compact prefiltered dataset, we are able to interactively apply any number of---potentially transformed---filters to a signal. Our performance scales linearly with the size of the decomposition, not the size nor the dimensionality of the filter, and our prefiltered data requires reasonnable storage, comparing favorably to the state-of-the-art. We apply IFD to interesting problems in image processing and realistic rendering.Les opérations de filtrage en synthèse/analyse d'images sont coûteuses à effectuer lorsque les filtres varient spatialement, sont très étendus et/ou très anisotropes. Nous présentons dans ce cas précis une méthode pour rendre le filtrage efficace, basée sur une décomposition du filtre en une combinaison linéaire de filtres isotropes, en translation. Le coût de notre méthode est linéaire par rapport au nombre de filtres utilisés dans la décomposition, et ne dépend pas de la taille des données filtrées. Nous en présentons différentes applications, en analyses d'images et en rendu

Edge-preserving Multiscale Image Decomposition based on Local Extrema

We propose a new model for detail that inherently captures oscillations, a key property that distinguishes textures from individual edges. Inspired by techniques in empirical data analysis and morphological image analysis, we use the local extrema of the input image to extract information about oscillations: We define detail as oscillations between local minima and maxima. Building on the key observation that the spatial scale of oscillations are characterized by the density of local extrema, we develop an algorithm for decomposing images into multiple scales of superposed oscillations. Current edge-preserving image decompositions assume image detail to be low contrast variation. Consequently they apply filters that extract features with increasing contrast as successive layers of detail. As a result, they are unable to distinguish between high-contrast, fine-scale features and edges of similar contrast that are to be preserved. We compare our results with existing edge-preserving image decomposition algorithms and demonstrate exciting applications that are made possible by our new notion of detail

A Theoretical Analysis of Compactness of the Light Transport Operator

International audienceRendering photorealistic visuals of virtual scenes requires tractable models for the simulation of light. The rendering equation describes one such model using an integral equation, the crux of which is a continuous integral operator. A majority of rendering algorithms aim to approximate the effect of this light transport operator via discretization (using rays, particles, patches, etc.). Research spanning four decades has uncovered interesting properties and intuition surrounding this operator. In this paper we analyze compactness, a key property that is independent of its discretization and which characterizes the ability to approximate the operator uniformly by a sequence of finite rank operators. We conclusively prove lingering suspicions that this operator is not compact and therefore that any discretization that relies on a finite-rank or nonadaptive finite-bases is susceptible to unbounded error over arbitrary light distributions. Our result justifies the expectation for rendering algorithms to be evaluated using a variety of scenes and illumination conditions. We also discover that its lower dimensional counterpart (over purely diffuse scenes) is not compact except in special cases, and uncover connections with it being noninvertible and acting as a low-pass filter. We explain the relevance of our results in the context of previous work. We believe that our theoretical results will inform future rendering algorithms regarding practical choices.Le rendu d'images photoréalistes de scènes virtuelles nécessite la simulation du transport lumineux. L'équation du rendu décrit un tel modèle à l'aide d'une équation intégrale, ou intervient un opérateur intégral continu. Une part significative des d'algorithmes de rendu visent à approximer l'effet de cet opérateur via une discrétisation (à l'aide de rayons, de particules, de patchs, etc.). Quatre décennies de recherches ont mis à jour des propriétés et une intuition entourant cet opérateur. Dans cet article, nous analysons sa compacité, une propriété clé qui est indépendante de la discrétisation et qui caractérise la possibilité d'approcher uniformément l'opérateur par une suite d'opérateurs de rang fini. Nous justifions les soupçons persistants que cet opérateur n'est pas compact et donc que toute discrétisation qui repose sur un rang fini ou des bases finies non adaptatives n'apporte pas de guarantie d'erreur sur des distributions de lumière arbitraires. Notre résultat justifie le besoin d'évaluer chaque méthode en utilisant une variété de scènes et de conditions d'éclairage. Nous montrons également que son homologue de dimension inférieure (sur des scènes purement diffuses) n'est pas compact sauf dans des cas particuliers, et établissons un lien avec le fait qu'il est non inversible et agit comme un filtre passe-bas. Nous expliquons la pertinence de nos résultats dans le contexte de travaux antérieurs. Nous pensons que nos résultats théoriques éclaireront les futurs algorithmes de rendu concernant les choix pratiques

A Generic Data Exchange System for Friend-to-Friend Networks

Decentralized private networks (a.k.a. darknets) guaranty privacy and concealment of information against global observers. Although a significant number of decentralized data distribution systems ex- ist, most of them target peer-to-peer architectures where any pair of nodes can exchange data using a temporary encrypted connection. Little has been done to achieve the same confidentiality in static darknet architectures, also known as “Friend-to-Friend” net- works, in which participants form a static mesh of nodes, each node only talking to a set of “friend” nodes managed by the user himself. Distributing data over F2F networks requires a specific model of confidentiality and proper algorithms in order to seamlessly spread the information beyond immediate friends nodes. In this paper we present a secure, robust and generic data distribution system that is specifically suitable to F2F networks. The proposed system manages pseudo-anonymous identities grouped into circles, that can be used to limit the access to information.It offers built-in reputation control and an abstract data layer to represent the information to spread. On top of that we present several existing applications to that system, providing the functionality of distributed forums, asynchroneous messaging, distribution channels, and also discuss the possibility to create social networking applications on top of it.Les réseaux privés décentralisés (ou Darknets) garrantissent la securite des informations contre l’espionnage de masse. Bien qu’une quantité significative de réseaux privés décentralisés existe dans le monde de l’open source, ceux ci sont généralement basés sur une architecture "pair à pair" (P2P) dans laquelle des communications directes sont succeptibles d’intervenir entre toutes les paires de noeud du réseau. Nous nous interessons plus particulièrement à la distribution sécurisée de données dans les réseaux de type "ami ami" (F2F), pour lesquels chaque noeud du réseau ne communique directement qu’avec une liste pré-déterminée de noeuds amis controllée par l’utilisateur. La distribution sécurisée de données sur ce type de réseau demande des algorithmes et un modèle de confidentialité adaptés adaptés Dans ce rapport, nous proposons un système robuste, sécurisé et extensible de distribution de données sur les réseaux F2F, proposant des identités pseudo-anonymes controllées par un système de réputations, et pouvant être regroupées en cercles d’amis pouvant être utilisés pour limiter la distribution des informations. Nous présentons plusieurs applications basées sur ce système, implémentant des forums, des chaines de distribution ainsi qu’une messagerie asynchrone

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

A physiological Plant Growth Simulation Engine Based on Accurate Radiant Energy Transfer

We present a new model for plant growth simulation, taking into account the eco-physiological processes driving plant development with unprecedented fidelity. The growth model, based on a physiological analysis, essentially simulates the internal function of the plant, and has been validated against measured biological data with excellent results. We show how to account for the influence of light through photosynthesis, and thereby incorporate the effects of a given plant's immediate environment on its architecture, shape and size. Since biological matter is controlled by water transpiration and received radiant enery, the model requires efficient and accurate simulation of radiant energy exchanges. We describe a complete lighting simulation system tailored for the difficult case of plants, by adapting state-of-the-art techniques such as hierarchical instanciation for radiosity and general BRDF modeling. Our results show that (a) our lighting simulation system efficiently provides the required information at the desired level of accuracy, and (b) the plant growth model is extremely well calibrated against real plants and (c) the combined system can simulate many interesting growth situations with direct feedback from the environment on the plant's characteristics. Applications range from landscape simulation to agronomical and agricultural studies, and to the design of virtual plants responding to their environment

Graphics Gems Revisited

International audienceWe present an algorithm for rendering faceted colored gemstones in real time, using graphics hardware. Beyond the technical challenge of handling the complex behavior of light in such objects, a real time high quality rendering of gemstones has direct applications in the field of jewelry prototyping, which has now become a standard practice for replacing tedious (and less interactive) wax carving methods. Our solution is based on a number of controlled approximations of the physical phenomena involved when light enters a stone, which permit an implementation based on the most recent -- yet commonly available -- hardware features such as fragment programs, cube-mapping and floating-point rendering

5D Covariance Tracing for Efficient Defocus and Motion Blur

The rendering of effects such as motion blur and depth-of-field requires costly 5D integrals. We dramatically accelerate their computation through adaptive sampling and reconstruction based on the prediction of the anisotropy and bandwidth of the integrand. For this, we develop a new frequency analysis of the 5D temporal light-field, and show that first-order motion can be handled through simple changes of coordinates in 5D. We further introduce a compact representation of the spectrum using the co- variance matrix and Gaussian approximations. We derive update equations for the 5 × 5 covariance matrices for each atomic light transport event, such as transport, occlusion, BRDF, texture, lens, and motion. The focus on atomic operations makes our work general, and removes the need for special-case formulas. We present a new rendering algorithm that computes 5D covariance matrices on the image plane by tracing paths through the scene, focusing on the single-bounce case. This allows us to reduce sampling rates when appropriate and perform reconstruction of images with complex depth-of-field and motion blur effects