Cyril Soler

A frequency analysis of light transport

We present a signal-processing framework for light transport. We study the frequency content of radiance and how it is altered by phenomena such as shading, occlusion, and transport. This extends previous work that considered either spatial or angular dimensions, and it offers a comprehensive treatment of both space and angle.We show that occlusion, a multiplication in the primal, amounts in the Fourier domain to a convolution by the spectrum of the blocker. Propagation corresponds to a shear in the space-angle frequency domain, while reflection on curved objects performs a different shear along the angular frequency axis. As shown by previous work, reflection is a convolution in the primal and therefore a multiplication in the Fourier domain. Our work shows how the spatial components of lighting are affected by this angular convolution.Our framework predicts the characteristics of interactions such as caustics and the disappearance of the shadows of small features. Predictions on the frequency content can then be used to control sampling rates for rendering. Other potential applications include precomputed radiance transfer and inverse rendering.

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.

Fast calculation of soft shadow textures using convolution

The calculation of detailed shadows remains one of the most difficult challenges in computer graphics, especially in the case of extended (linear or area) light sources. This paper introduces a new tool for the calculation of shadows cast by extended light sources. Exact shadows are computed in some constrained configurations by using a convolution technique, yielding a fast and accurate solution. Approximate shadows can be computed for general configurations by applying the convolution to a representative “ideal” configuration. We analyze the various sources of approximation in the process and derive a hierarchical, error driven algorithm for fast shadow calculation in arbitrary configurations using a hierarchy of object clusters. The convolution is performed on images rendered in an offscreen buffer and produces a shadow map used as a texture to modulate the unoccluded illumination. Light sources can have any 3D shape as well as arbitrary emission characteristics, while shadow maps can be applied to groups of objects at once. The method can be employed in a hierarchical radiosity system, or directly as a shadowing technique. We demonstrate results for various scenes, showing that soft shadows can be generated at interactive rates for dynamics environments.

Hierarchical pattern mapping

We present a multi-scale algorithm for mapping a texture defined by an input image onto an arbitrary surface. It avoids the generation and storage of a new, specific texture. The idea is to progressively cover the surface by texture patches of various sizes and shapes, selected from a single input image. The process starts with large patches. A mapping that minimizes the texture fitting error with already textured neighbouring patches is selected. When this error is above a threshold, the patch is split into smaller ones, and the algorithm recursively looks for good fits at a smaller scale. The process ends when the surface is entirely covered. Our results show that the method correctly handles a wide set of texture patterns, which can be used at different mapping scales. Hierarchical texture mapping only outputs texture coordinates in the original texture for each triangle of the initial mesh. Rendering is therefore easy and memory cost minimal. Moreover the initial geometry is preserved.

Accurate detection of symmetries in 3D shapes

We propose an automatic method for finding symmetries of 3D shapes, that is, isometric transforms which leave a shape globally unchanged. These symmetries are deterministically found through the use of an intermediate quantity: the generalized moments. By examining the extrema and spherical harmonic coefficients of these moments, we recover the parameters of the symmetries of the shape. The computation for large composite models is made efficient by using this information in an incremental algorithm capable of recovering the symmetries of a whole shape using the symmetries of its subparts. Applications of this work range from coherent remeshing of geometry with respect to the symmetries of a shape to geometric compression, intelligent mesh editing, and automatic instantiation.

An efficient instantiation algorithm for simulating radiant energy transfer in plant models

We describe a complete lighting simulation system tailored for the difficult case of vegetation scenes. Our algorithm is based on hierarchical instantiation for radiosity and precise phase function modeling. It allows efficient calculations both in terms of computation and memory resources. We provide an in-depth description and study of the instantiation-based radiosity technique and we address the problems related to generating and managing phase functions of plant structures, as needed by the instantiation process. We present results demonstrating the high performance of the hierarchical instantiation algorithm and we describe two examples of applications: rendering of large vegetation scenes and plant growth simulation. Other applications of our system range from landscape simulation to agronomical and agricultural studies, and to the design of virtual plants responding to their environment.

Fourier depth of field

Optical systems used in photography and cinema produce depth-of-field effects, that is, variations of focus with depth. These effects are simulated in image synthesis by integrating incoming radiance at each pixel over the lense aperture. Unfortunately, aperture integration is extremely costly for defocused areas where the incoming radiance has high variance, since many samples are then required for a noise-free Monte Carlo integration. On the other hand, using many aperture samples is wasteful in focused areas where the integrand varies little. Similarly, image sampling in defocused areas should be adapted to the very smooth appearance variations due to blurring. This article introduces an analysis of focusing and depth-of-field in the frequency domain, allowing a practical characterization of a light fields frequency content both for image and aperture sampling. Based on this analysis we propose an adaptive depth-of-field rendering algorithm which optimizes sampling in two important ways. First, image sampling is based on conservative bandwidth prediction and a splatting reconstruction technique ensures correct image reconstruction. Second, at each pixel the variance in the radiance over the aperture is estimated and used to govern sampling. This technique is easily integrated in any sampling-based renderer, and vastly improves performance.

A Clustering Algorithm for Radiance Calculation In General Environments

This paper introduces an efficient hierarchical algorithm capable of simulating light transfer for complex scenes containing non-diffuse surfaces. The algorithm stems from a new formulation of hierarchical energy exchangesbetween object clusters, based on the explicit representation of directional radiometric distributions. This approach permits the simplified evaluation of energy transfers and error bounds between clusters. Representation and storage issues are central to this type of algorithm: we discuss the different choices for representing directional distributions, and the choice between explicit storage or immediate propagation of directional information in the hierarchy. The framework presented is well suited to a multi-resolution representation, which may in turn significantly alleviate the storage problems. Results from an implementation are presented, indicating the feasibility of the approach and its capacity to treat complex scenes

Graphics gems revisited: fast and physically-based rendering of gemstones

We 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.

Recent Advances in Adaptive Sampling and Reconstruction for Monte Carlo Rendering

Monte Carlo integration is firmly established as the basis for most practical realistic image synthesis algorithms because of its flexibility and generality. However, the visual quality of rendered images often suffers from estimator variance, which appears as visually distracting noise. Adaptive sampling and reconstruction algorithms reduce variance by controlling the sampling density and aggregating samples in a reconstruction step, possibly over large image regions. In this paper we survey recent advances in this area. We distinguish between “a priori” methods that analyze the light transport equations and derive sampling rates and reconstruction filters from this analysis, and “a posteriori” methods that apply statistical techniques to sets of samples to drive the adaptive sampling and reconstruction process. They typically estimate the errors of several reconstruction filters, and select the best filter locally to minimize error. We discuss advantages and disadvantages of recent state‐of‐the‐art techniques, and provide visual and quantitative comparisons. Some of these techniques are proving useful in real‐world applications, and we aim to provide an overview for practitioners and researchers to assess these approaches. In addition, we discuss directions for potential further improvements.