Abstract The visual fidelity of realistic renderings in Computer Graphics depends fundamentally upon how we model the appearance of objects resulting from the interaction between light and matter reaching the eye. In this paper, we survey the research addressing appearance modelling of living human tissue. Among the many classes of natural materials already researched in Computer Graphics, living human tissues such as blood and skin have recently seen an increase in attention from graphics research. There is already an incipient but substantial body of literature on this topic, but we also lack a structured review as presented here. We introduce a classification for the approaches using the four types of human tissues as classifiers. We show a growing trend of solutions that use first principles from Physics and Biology as fundamental knowledge upon which the models are built. The organic quality of visual results provided by these Biophysical approaches is mainly determined by the optical properties of biophysical components interacting with light. Beyond just picture making, these models can be used in predictive simulations, with the potential for impact in many other areas.

A method is presented for perceptually characterizing appearance non-uniformities that result from 3D printing. In contrast to physical measurements, the model is designed to take into account the human visual system and variations in observer conditions such as lighting, point of view, and shape. Additionally, it is capable of handling spatial reflectance variations over a material's surface. Motivated by Schrödinger's line element approach to studying color differences, an image-based psychophysical experiment that explores paths between materials in appearance space is conducted. The line element concept is extended from color to spatially-varying appearances-including color, roughness and gloss-which enables the measurement of fine differences between appearances along a path. We define two path functions, one interpolating reflectance parameters and the other interpolating the final imagery. An image-based uniformity model is developed, applying a trained neural network to color differences calculated from rendered images of the printed non-uniformities. The final model is shown to perform better than commonly used image comparison algorithms, including spatial pattern classes that were not used in training.

Abstract Robust statistical methods are employed to reduce the noise in Monte Carlo ray tracing. Through the use of resampling, the sample mean distribution is determined for each pixel. Because this distribution is uni‐modal and normal for a large sample size, robust estimates converge to the true mean of the pixel values. Compared to existing methods, less additional storage is required at each pixel because the sample mean distribution can be distilled down to a compact size, and fewer computations are necessary because the robust estimation process is sampling independent and needs a small input size to compute pixel values. The robust statistical pixel estimators are not only resistant to impulse noise, but they also remove general noise from fat‐tailed distributions. A substantial speedup in rendering can therefore be achieved by reducing the number of samples required for a desired image quality. The effectiveness of the proposed approach is demonstrated for path tracing simulations.

Abstract The propagation and reflection of electromagnetic waves in a three‐dimensional environment is simulated, and realistic images are produced using the resulting light distributions and reflectance functions. A finite difference time domain method is employed to advance the electric and magnetic fields in a scene. Surfaces containing wavelength scaled structures are created, the interaction of the electromagnetic waves with these nano‐structured materials is calculated, and the sub‐surface interference and diffraction effects are modelled. The result is a reflectance function with wavelength composition and spatial distribution properties that could not have been predicted using classic computer graphic ray tracing approaches. The techniques are employed to reproduce demonstrations of simple interference and diffraction effects, and to create computer‐generated pictures of a Morpho butterfly.

A system is introduced for the simulation of spray painting. Head mounted display goggles are combined with a tracking system to allow users to paint a virtual surface with a spray gun. Ray tracing is used to simulate droplets landing on the surface of the object, allowing arbitrary shapes and spray gun patterns to be used. This system is combined with previous research on spray gun characteristics to provide a realistic simulation of the spray paint including the effects of viscosity, air pressure, and paint pressure. The simulation provides two different output modes: a non-photorealistic display that gives a visual representation of how much paint has landed on the surface, and a photorealistic simulation of how the paint would actually look on the object once it dried. Useful feedback values such as overspray are given. Experiments were performed to validate the system.

The properties of the human visual system are taken into account, along with the geometric aspects of an object, in a new surface remeshing algorithm and a new mesh simplification algorithm. Both algorithms have a preprocessing step and are followed by the remeshing or mesh simplification steps. The preprocessing step computes an importance map that indicates the visual masking potential of the visual patterns on the surface. The importance map is then used to guide the remeshing or mesh simplification algorithms. Two different methods are proposed for computing an importance map that indicates the masking potential of the visual patterns on the surface. The first one is based on the Sarnoff visual discrimination metric, and the second one is inspired by the visual masking tool available in the current JPEG2000 standard. Given an importance map, the surface remeshing algorithm automatically distributes few samples to surface regions with strong visual masking properties due to surface texturing, lighting variations, bump mapping, surface reflectance and inter-reflections. Similarly, the mesh simplification algorithm simplifies more aggressively where the light field of an object can hide more geometric artifacts.

The faceting signal, defined in this paper as the difference signal between a rendering of the original geometric model and a simplified version of the geometric model, is responsible for the faceting artifacts commonly observed in the renderings of coarse geometric models. In this paper, we analyze the source of the faceting signal and develop a perceptual metric for the visibility of the faceting signal.

Visual patterns on the surface of an object, such as two dimensional texture, are taken into consideration as part of the geometry remeshing process. Given a parameterized mesh and a texture map, the visual perceptual properties of the texture are first computed using a visual discrimination metric. This precomputation is then used to guide the distribution of samples to the surface mesh. The system automatically distributes few samples to texture areas with strong visual masking properties and more samples to texture areas with weaker visual masking properties. In addition, due to contrast considerations, brighter areas receive fewer samples than do darker surface features. Because of the properties of the human visual system, especially visual masking, the artifacts in the rendered mesh are invisible to the human observer. For a fixed number of polygons, this approach also improves the quality of the rendered mesh since the distribution of the samples is guided by the principles of visual perception. The utility of the system is demonstrated by showing that it can also account for other observable patterns on the surface, besides two dimensional texture, such as those produced by bump mapping, lighting variations, surface reflectance, and interreflections.

A new close range virtual reality system is introduced that allows intuitive and immersive user interaction with computer generated objects. A projector with a special spherical lens is combined with a flexible, tracked rear projection screen that users hold in their hands. Unlike normal projectors, the spherical lens allows for a 180 degree field of view and nearly infinite depth of focus. This allows the user to move the screen around the environment and use it as a virtual "slice" to examine the interior of 3D volumes. This provides a concrete correspondence between the virtual representation of the 3D volume and how that volume would actually appear if its real counterpart was sliced open. The screen can also be used as a "magic window" to view the mesh of the volume from different angles prior to taking cross sections of it. Real time rendering of the desired 3D volume or mesh is accomplished using current graphics hardware. Additional applications of the system are also discussed.

Appearance standards for gloss, haze, and goniochromatic color are applied to computer graphic reflection models. Correspondences are derived between both the gloss and haze standards and the specular exponent of the Phong model, the surface roughness of the Ward model, and the surface roughness of the Cook-Torrance model. Metallic and pearlescent colors are rendered using three aspecular measurements defined in a proposed standard for goniochromatic color. The reflection models for gloss and goniochromatic color are combined to synthesize pictures of clear coated automotive paint. Advantages of using appearance standards to select reflection model parameters include the small number of required measurements and the inexpensive commercially available instruments necessary to acquire the data. The use of a standard appearance scale also provides a more intuitive way of selecting the reflection model parameters and a reflection model independent method of specifying appearance.

A perceptually based approach for selecting image samples has been developed.An existing image processing vision model has been extended to handle color and has been simplified to run efficiently.The resulting new image quality model was inserted into an image synthesis program by first modifying the rendering algorithm so that it computed a wavelet representation.In addition to allowing image quality to be determined as the image was generated, the wavelet representation made it possible to use statistical information about the spatial frequency distribution of natural images to estimate values where samples were yet to be taken.Tests on the image synthesis algorithm showed that it correctly handled achromatic and chromatic spatial detail and that it was able predict and compensate for masking effects.The program was also shown to produce images of equivalent visual quality while using different rendering techniques.

A ray tracer has been developed that synthesizes images directly into the frequency domain.This makes it possible to use a simple vision model to control where rays are cast into a scene and to decide how rays should be spawned once an object is intersected.In this manner the most visible artifacts can be removed first and noise can be channeled into those areas of an image where it is least noticeable.The resulting image is produced in a format that is consistent with many image compression and transmission schemes.

A wavelength based bidirectional reflectance function is developed for use in realistic image synthesis. A geodesic sphere is employed to represent the BRDF, and a novel data structure is used to store this description and to recall it for rendering purposes. A virtual goniospectrophotometer is implemented by using a Monte Carlo ray tracer to cast rays into a surface. An optics model that incorporates phase is used in the ray tracer to simulate interference effects. An adaptive subdivision technique is applied to elaborate the data structure from rays scattered into the hemisphere above the surface. The wavelength based BRDF and virtual goniospectrophotometer are utilized to analyze and make pictures of thin films, idealized pigmented materials, and pearlescent paints.

This article discusses and applies the Kubelka-Munk theory of pigment mixing to computer graphics in order to facilitate improved image synthesis. The theories of additive and subtractive color mixing are discussed and are shown to be insufficient for pigmented materials. The Kubelka–Munk theory of pigment mixing is developed and the relevant equations are derived. Pigment mixing experiments are performed and the results are displayed on color television monitors. A paint program that uses Kubelka–Munk theory to mix real pigments is presented. Theories of color matching with pigments are extended to determine reflectances for use in realistic image synthesis.

No abstract available.

The efficient synthesis of color in computer graphics is dependent on modelling the correct number and spacing of wavelengths across the visible spectrum. It has recently been shown that the opponent representation of the fundamental spectral sensitivity functions is optimal from the point of view of statistical communication theory. This result is used in this paper to guide the selection of wavelengths for synthetic image generation. Gaussian quadrature with the opponent fundamentals as weighting functions is used to choose the wavelengths. This approach is shown to be superior to using Gaussian quadrature with the fundamental spectral sensitivity functions or the CIE XYZ matching functions. The technique is evaluated by using color difference calculations and by comparisons between a real scene and a computer generated picture of that scene.

Accurate simulation of light propagation within an environment and perceptually based imaging techniques are necessary for the creation of realistic images. A physical experiment that verifies the simulation of reflected light intensities for diffuse environments was conducted. Measurements of radiant energy flux densities are compared with predictions using the radiosity method for those physical environments. By using color science procedures the results of the light model simulation are then transformed to produce a color television image. The final image compares favorably with the original physical model. The experiment indicates that, when the physical model and the simulation were viewed through a view camera, subjects could not distinguish between them. The results and comparison of both test procedures are presented within this paper.

Perceptually uniform color spaces can be a useful tool for solving computer graphics color selection problems. However, before they can be used effectively some basic principles of tristimulus colorimetry must be understood and the color reproduction device on which they are to be used must be properly adjusted. The Munsell Book of Color and the Optical Society of America (OSA) Uniform Color Scale are two uniform color spaces which provide a useful way of organizing the colors of a digitally controlled color television monitor. The perceptual uniformity of these color spaces can be used to select color scales to encode the variations of parameters such as temperature or stress.