Bruce Walter

Lightcuts: a scalable approach to illumination

Lightcuts is a scalable framework for computing realistic illumination. It handles arbitrary geometry, non-diffuse materials, and illumination from a wide variety of sources including point lights, area lights, HDR environment maps, sun/sky models, and indirect illumination. At its core is a new algorithm for accurately approximating illumination from many point lights with a strongly sublinear cost. We show how a group of lights can be cheaply approximated while bounding the maximum approximation error. A binary light tree and perceptual metric are then used to adaptively partition the lights into groups to control the error vs. cost tradeoff.We also introduce reconstruction cuts that exploit spatial coherence to accelerate the generation of anti-aliased images with complex illumination. Results are demonstrated for five complex scenes and show that lightcuts can accurately approximate hundreds of thousands of point lights using only a few hundred shadow rays. Reconstruction cuts can reduce the number of shadow rays to tens.

Microfacet models for refraction through rough surfaces

Microfacet models have proven very successful for modeling light reflection from rough surfaces. In this paper we review microfacet theory and demonstrate how it can be extended to simulate transmission through rough surfaces such as etched glass. We compare the resulting transmission model to measured data from several real surfaces and discuss appropriate choices for the microfacet distribution and shadowing-masking functions. Since rendering transmission through media requires tracking light that crosses at least two interfaces, good importance sampling is a practical necessity. Therefore, we also describe efficient schemes for sampling the microfacet models and the corresponding probability density functions.

Interactive rendering using the render cache

Interactive rendering requires rapid visual feedback. The render cache is a new method for achieving this when using high-quality pixel-oriented renderers such as ray tracing that are usually considered too slow for interactive use. The render cache provides visual feedback at a rate faster than the renderer can generate complete frames, at the cost of producing approximate images during camera and object motion. The method works both by caching previous results and reprojecting them to estimate the current image and by directing the renderers sampling to more rapidly improve subsequent images. Our implementation demonstrates an interactive application working with both ray tracing and path tracing renderers in situations where they would normally be considered too expensive. Moreover we accomplish this using a software only implementation without the use of 3D graphics hardware.

A framework for realistic image synthesis

Our goal is to develop physically based lighting models and perceptually based rendering procedures for computer graphics that will produce synthetic images that are visually and measurably indistinguishable from real-world images. Fidelity of the physical simulation is of primary concern. Our research framework is subdivided into three sub-sections: the local light reflection model, the energy transport simulation, and the visual display algorithms. The first two subsections are physically based, and the last is perceptually based. We emphasize the comparisons between simulations and actual measurements, the difficulties encountered, and the need to utilize the vast amount of psychophysical research already conducted. Future research directions are enumerated. We hope that results of this research will help establish a more fundamental, scientific approach for future rendering algorithms. This presentation describes a chronology of past research in global illumination and how parts of our new system are currently being developed.

Visual equivalence: towards a new standard for image fidelity

Efficient, realistic rendering of complex scenes is one of the grand challenges in computer graphics. Perceptually based rendering addresses this challenge by taking advantage of the limits of human vision. However, existing methods, based on predicting visible image differences, are too conservative because some kinds of image differences do not matter to human observers. In this paper, we introduce the concept of visual equivalence, a new standard for image fidelity in graphics. Images are visually equivalent if they convey the same impressions of scene appearance, even if they are visibly different. To understand this phenomenon, we conduct a series of experiments that explore how object geometry, material, and illumination interact to provide information about appearance, and we characterize how two kinds of transformations on illumination maps (blurring and warping) affect these appearance attributes. We then derive visual equivalence predictors (VEPs): metrics for predicting when images rendered with transformed illumination maps will be visually equivalent to images rendered with reference maps. We also run a confirmatory study to validate the effectiveness of these VEPs for general scenes. Finally, we show how VEPs can be used to improve the efficiency of two rendering algorithms: Light-cuts and precomputed radiance transfer. This work represents some promising first steps towards developing perceptual metrics based on higher order aspects of visual coding.

Multidimensional lightcuts

Multidimensional lightcuts is a new scalable method for efficiently rendering rich visual effects such as motion blur, participating media, depth of field, and spatial anti-aliasing in complex scenes. It introduces a flexible, general rendering framework that unifies the handling of such effects by discretizing the integrals into large sets of gather and light points and adaptively approximating the sum of all possible gather-light pair interactions.We create an implicit hierarchy, the product graph, over the gather-light pairs to rapidly and accurately approximate the contribution from hundreds of millions of pairs per pixel while only evaluating a tiny fraction (e.g., 200--1,000). We build upon the techniques of the prior Lightcuts method for complex illumination at a point, however, by considering the complete pixel integrals, we achieve much greater efficiency and scalability.Our example results demonstrate efficient handling of volume scattering, camera focus, and motion of lights, cameras, and geometry. For example, enabling high quality motion blur with 256x temporal sampling requires only a 6.7x increase in shading cost in a scene with complex moving geometry, materials, and illumination.

Interactive global illumination in dynamic scenes

In this paper, we present a system for interactive computation of global illumination in dynamic scenes. Our system uses a novel scheme for caching the results of a high quality pixel-based renderer such as a bidirectional path tracer. The Shading Cache is an object-space hierarchical subdivision mesh with lazily computed shading values at its vertices. A high frame rate display is generated from the Shading Cache using hardware-based interpolation and texture mapping. An image space sampling scheme refines the Shading Cache in regions that have the most interpolation error or those that are most likely to be affected by object or camera motion.Our system handles dynamic scenes and moving light sources efficiently, providing useful feedback within a few seconds and high quality images within a few tens of seconds, without the need for any pre-computation. Our approach allows us to significantly outperform other interactive systems based on caching ray-tracing samples, especially in dynamic scenes. Based on our results, we believe that the Shading Cache will be an invaluable tool in lighting design and modelling while rendering.

Global Illumination via Density-Estimation

This paper presents a new method for the production of view-independent global illumi-nation solutions of complex static environments. A key innovation of this new approach is its decomposition of the problem into a loosely coupled sequence of simple modules. This approach decouples the global energy transport computation from the construction of the displayable shaded representation of the environment. This decoupling eliminates many constraints of previous global illumination approaches, yielding accurate solutions for environments with non-diffuse surfaces and high geometric complexity.

Global illumination using local linear density estimation

This article presents the density estimation framework for generating view-independent global illumination solutions. It works by probabilistically simulating the light flow in an environment with light particles that trace random walks origination at luminaires and then using statistical density estimation techniques to reconstruct the lighting on each surface. By splitting the computation into separate transport and reconstruction stages, we gain many advantages including reduced memory usage, the ability to simulate nondiffuse transport, and natural parallelism. Solutions to several theoretical and practical difficulties in implementing this framework are also described. Light sources that vary spectrally and directionally are integrated into a spectral particle tracer using nonuniform rejection. A new local linear density estimation technique eliminates boundary bias and extends to arbitrary polygons. A mesh decimation algorithm with perceptual calibration is introduced to simplify the Gouraud-shaded representation of the solution for interactive display.

Fast agglomerative clustering for rendering

Hierarchical representations of large data sets, such as binary cluster trees, are a crucial component in many scalable algorithms used in various fields. Two major approaches for building these trees are agglomerative, or bottom-up, clustering and divisive, or top-down, clustering. The agglomerative approach offers some real advantages such as more flexible clustering and often produces higher quality trees, but has been little used in graphics because it is frequently assumed to be prohibitively expensive (O(N2) or worse). In this paper we show that agglomerative clustering can be done efficiently even for very large data sets. We introduce a novel locally-ordered algorithm that is faster than traditional heap-based agglomerative clustering and show that the complexity of the tree build time is much closer to linear than quadratic. We also evaluate the quality of the agglomerative clustering trees compared to the best known divisive clustering strategies in two sample applications: bounding volume hierarchies for ray tracing and light trees in the Lightcuts rendering algorithm. Tree quality is highly application, data set, and dissimilarity function specific. In our experiments the agglomerative-built tree quality is consistently higher by margins ranging from slight to significant, with up to 35% reduction in tree query times.