Photorealistic and physically-based rendering of real-world environments with high fidelity materials is important to a range of applications, including special effects, architectural modelling, cultural heritage, computer games, automotive design, and virtual reality (VR). Our perception of the world depends on lighting and surface material characteristics, which determine how the light is reflected, scattered, and absorbed. In order to reproduce appearance, we must therefore understand all the ways objects interact with light, and the acquisition and representation of materials has thus been an important part of computer graphics from early days. Nevertheless, no material model nor acquisition setup is without limitations in terms of the variety of materials represented, and different approaches vary widely in terms of compatibility and ease of use.

We present a technique for displaying three-dimensional imagery of general scenes with nearly correct focus cues on multi-plane displays. These displays present an additive combination of images at a discrete set of optical distances, allowing the viewer to focus at different distances in the simulated scene. Our proposed technique extends the capabilities of multi-plane displays to general scenes with occlusions and non-Lambertian effects by using a model of defocus in the eye of the viewer. Requiring no explicit knowledge of the scene geometry, our technique uses an optimization algorithm to compute the images to be displayed on the presentation planes so that the retinal images when accommodating to different distances match the corresponding retinal images of the input scene as closely as possible. We demonstrate the utility of the technique using imagery acquired from both synthetic and real-world scenes, and analyze the system's characteristics including bounds on achievable resolution.

Capturing detailed surface geometry currently requires specialized equipment such as laser range scanners, which despite their high accuracy, leave gaps in the surfaces that must be reconciled with photographic capture for relighting applications. Using only a standard digital camera and a single view, we present a method for recovering models of predominantly diffuse textured surfaces that can be plausibly relit and viewed from any angle under any illumination. Our multiscale shape-from-shading technique uses diffuse-lit/flash-lit image pairs to produce an albedo map and textured height field. Using two lighting conditions enables us to subtract one from the other to estimate albedo. In the absence of a flash-lit image of a surface for which we already have a similar exemplar pair, we approximate both albedo and diffuse shading images using histogram matching. Our depth estimation is based on local visibility. Unlike other depth-from-shading approaches, all operations are performed on the diffuse shading image in image space, and we impose no constant albedo restrictions. An experimental validation shows our method works for a broad range of textured surfaces, and viewers are frequently unable to identify our results as synthetic in a randomized presentation. Furthermore, in side-by-side comparisons, subjects found a rendering of our depth map equally plausible to one generated from a laser range scan. We see this method as a significant advance in acquiring surface detail for texturing using a standard digital camera, with applications in architecture, archaeological reconstruction, games and special effects.

Monte Carlo techniques for image synthesis are simple and powerful, but they are prone to noise from inadequate sampling. This paper describes a class of non-linear filters that remove sampling noise in synthetic images without removing salient features. This is achieved by spreading real input sample values into the output image via variable-width filter kernels, rather than gathering samples into each output pixel via a constant-width kernel. The technique is nonlinear because kernel widths are based on sample magnitudes, and this local redistribution of values cannot generally be mapped to a linear function. Nevertheless, the technique preserves energy because the kernels are normalized, and all input samples have the same average influence on the output. To demonstrate its effectiveness, the new filtering method is applied to two rendering techniques. The first is a Monte Carlo path tracing technique with the conflicting goals of keeping pixel variance below a specified limit and finishing in a finite amount of time; this application shows how the filter may be used to “clean up” areas where it is not practical to sample adequately. The second is a hybrid deterministic and Monte Carlo ray-tracing program; this application shows how the filter can be effective even when the pixel variance is not known.

This paper describes a physically-based rendering system tailored to the demands of lighting design and architecture. The simulation uses a light-backwards ray-tracing method with extensions to efficiently solve the rendering equation under most conditions. This includes specular, diffuse and directional-diffuse reflection and transmission in any combination to any level in any environment, including complicated, curved geometries. The simulation blends deterministic and stochastic ray-tracing techniques to achieve the best balance between speed and accuracy in its local and global illumination methods. Some of the more interesting techniques are outlined, with references to more detailed descriptions elsewhere. Finally, examples are given of successful applications of this free software by others.

A new device for measuring the spatial reflectancedistributionsof surfaces is introduced, along with a new mathematical model of sniaorropic reflectance.The reflectance model presented is both simple and accurate, permitting efficient reflectance data reduction rasd reproduction.Tire validity of the model is substantiated with comparisons to complete meaarsremems of surface reflectance functions gathered with the novel retlectometry device.This new device uses imaging technology to capture the entire hemisphem of reflected directions simttkarreously, which greatly accelerates the reflectance data gathering process, making it pssible to measure dozens of surfaces in the time that it used to take to do one.Example measurements and simulations are shown.and a table of fitted parameters for several surfaces is presented.

An efficient ray tracing method is presented for calculating interreflections between surfaces with both diffuse and specular components. A Monte Carlo technique computes the indirect contributions to illuminance at locations chosen by the rendering process. The indirect illuminance values are averaged over surfaces and used in place of a constant "ambient" term. Illuminance calculations are made only for those areas participating in the selected view, and the results are stored so that subsequent views can reuse common values. The density of the calculation is adjusted to maintain a constant accuracy, permitting less populated portions of the scene to be computed quickly. Successive reflections use proportionally fewer samples, which speeds the process and provides a natural limit to recursion. The technique can also model diffuse transmission and illumination from large area sources, such as the sky.