Jeppe Revall Frisvad

Computing the scattering properties of participating media using Lorenz-Mie theory

This paper introduces a theoretical model for computing the scattering properties of participating media and translucent materials. The model takes as input a description of the components of a medium and computes all the parameters necessary to render it. These parameters are the extinction and scattering coefficients, the phase function, and the index of refraction, Our theory is based on a robust generalization of the Lorenz-Mie theory. Previous models using Lorenz-Mie theory have been limited to non-absorbing media with spherical particles such as paints and clouds. Our generalized theory is capable of handling both absorbing host media and non-spherical particles, which significantly extends the classes of media and materials that can be modeled. We use the theory to computer optical properties for different types of ice and ocean water, and we derive a novel appearance model for milk parameterized by the fat and protein contents. Our results show that we are able to match measured scattering properties in cases where the classical Lorez-Mie theory breaks down, and we can compute properties for media that cannot be measured using existing techniques in computer graphics.

Temporal Glare: Real-Time Dynamic Simulation of the Scattering in the Human Eye

Glare is a consequence of light scattered within the human eye when looking at bright light sources. This effect can be exploited for tone mapping since adding glare to the depiction of high‐dynamic range (HDR) imagery on a low‐dynamic range (LDR) medium can dramatically increase perceived contrast. Even though most, if not all, subjects report perceiving glare as a bright pattern that fluctuates in time, up to now it has only been modeled as a static phenomenon. We argue that the temporal properties of glare are a strong means to increase perceived brightness and to produce realistic and attractive renderings of bright light sources. Based on the anatomy of the human eye, we propose a model that enables real‐time simulation of dynamic glare on a GPU. This allows an improved depiction of HDR images on LDR media for interactive applications like games, feature films, or even by adding movement to initially static HDR images. By conducting psychophysical studies, we validate that our method improves perceived brightness and that dynamic glare‐renderings are often perceived as more attractive depending on the chosen scene.

Photon differentials

A number of popular global illumination algorithms uses density estimation to approximate indirect illumination. The density estimate is performed on finite points -- particles -- generated by a stochastic sampling of the scene. In the course of the sampling, particles, representing light, are stochastically emitted from the light sources and reflected around the scene. The sampling induces noise, which in turn is handled by the density estimate during the illumination reconstruction. Unfortunately, this noise reduction imposes a systematic error (bias), which is seen as a blurring of prominent illumination features. This is often not desirable as these may lose clarity or vanish altogether. We present an accurate method for reconstruction of indirect illumination with photon mapping. Instead of reconstructing illumination using classic density estimation on finite points, we use the correlation of light footprints, created by using Ray Differentials during the light pass. This procedure gives a high illumination accuracy, improving the trade-off between bias and variance considerable as compared to traditional particle tracing algorithms. In this way we preserve structures in indirect illumination.

Directional Dipole Model for Subsurface Scattering

Rendering translucent materials using Monte Carlo ray tracing is computationally expensive due to a large number of subsurface scattering events. Faster approaches are based on analytical models derived from diffusion theory. While such analytical models are efficient, they miss out on some translucency effects in the rendered result. We present an improved analytical model for subsurface scattering that captures translucency effects present in the reference solutions but remaining absent with existing models. The key difference is that our model is based on ray source diffusion, rather than point source diffusion. A ray source corresponds better to the light that refracts through the surface of a translucent material. Using this ray source, we are able to take the direction of the incident light ray and the direction toward the point of emergence into account. We use a dipole construction similar to that of the standard dipole model, but we now have positive and negative ray sources with a mirrored pair of directions. Our model is as computationally efficient as existing models while it includes single scattering without relying on a separate Monte Carlo simulation, and the rendered images are significantly closer to the references. Unlike some previous work, our model is fully analytic and requires no precomputation.

State of the art in photon density estimation

Photon-density estimation techniques are a popular choice for simulating light transport in scenes with complicated geometry and materials. This class of algorithms can be used to accurately simulate inter-reflections, caustics, color bleeding, scattering in participating media, and subsurface scattering. Since its introduction, photon-density estimation has been significantly extended in computer graphics with the introduction of: specialized techniques that intelligently modify the positions or bandwidths to reduce visual error using a small number of photons, approaches that eliminate error completely in the limit, and methods that use higher-order samples and queries to reduce error in participating media. This two-part course explains how to implement all these latest advances in photon-density estimation. It begins with a short introduction using classical photon mapping, but the remainder of the course provides new, hands-on explanations of the latest developments in this area by experts in each technique. Attendees gain concrete and practical understanding of the latest developments in photon-density-estimation techniques that have not been presented before in SIGGRAPH courses.

Non-invasive assessment of dairy products using spatially resolved diffuse reflectance spectroscopy.

The quality of a dairy product is largely determined by its microstructure which also affects its optical properties. Consequently, an assessment of the optical properties during production may be part of a feedback system for ensuring the quality of the production process. This paper presents a novel camera-based measurement technique that enables robust quantification of a wide range of reduced scattering coefficients and absorption coefficients. Measurements are based on hyperspectral images of diffuse reflectance in the wavelength range of 470 to 1020 nm. The optical properties of commercially available milk and yogurt products with three different levels of fat content are measured. These constitute a relevant range of products at a dairy plant. The measured reduced scattering properties of the samples are presented and show a clear discrimination between levels of fat contents as well as fermentation. The presented measurement technique and method of analysis is thus suitable for a rapid, non-contact, and non-invasive inspection that can deduce physically interpretable properties.

Building an Orthonormal Basis from a 3D Unit Vector Without Normalization

Abstract I present two tools that save the computation of a dot product and a reciprocal square root in operations that are used frequently in the core of many rendering programs. The first tool is a formula for rotating a direction sampled around the z-axis to a direction sampled around an arbitrary unit vector. This is useful in Monte Carlo rendering techniques, such as path tracing, where directions are usually sampled in spherical coordinates and then transformed to a Cartesian unit vector in a local coordinate system where the zenith direction is the z-axis. The second tool is a more general result extracted from the first formula, namely a faster way of building an orthonormal basis from a 3D unit vector. These tools require fewer arithmetic operations than other methods I am aware of, and a performance test of the more general tool confirms that it is faster.

Fast high-quality noise

At the moment the noise functions available in a graphics programmers toolbox are either slow to compute or they involve grid-line artifacts making them of lower quality. In this paper we present a real-time noise computation with no grid-line artifacts or other regularity problems. In other words, we put a new tool in the box that computes fast high-quality noise. In addition to being free of artifacts, the noise we present does not rely on tabulated data (everything is computed on the fly) and it is easy to adjust quality vs. quantity for the noise. The noise is based on point rendering (like spot noise), but it extends to more than two dimensions. The fact that it is based on point rendering makes art direction of the noise much easier.

Noninvasive particle sizing using camera-based diffuse reflectance spectroscopy

Diffuse reflectance measurements are useful for noninvasive inspection of optical properties such as reduced scattering and absorption coefficients. Spectroscopic analysis of these optical properties can be used for particle sizing. Systems based on optical fiber probes are commonly employed, but their low spatial resolution limits their validity ranges for the coefficients. To cover a wider range of coefficients, we use camera-based spectroscopic oblique incidence reflectometry. We develop a noninvasive technique for acquisition of apparent particle size distributions based on this approach. Our technique is validated using stable oil-in-water emulsions with a wide range of known particle size distributions. We also measure the apparent particle size distributions of complex dairy products. These results show that our tool, in contrast to those based on fiber probes, can deal with a range of optical properties wide enough to track apparent particle size distributions in a typical industrial process.

Predicting the Appearance of Materials Using Lorenz–Mie Theory

Computer graphics systems today are able to produce highly realistic images. The realism has reached a level where an observer has difficulties telling whether an image is real or synthetic. The exception is when we try to compute a picture of a scene that really exists and compare the result to a photograph of the real scene. In this direct comparison, an observer quickly identifies the synthetic image. One of the problems is to model all the small geometrical details correctly. This is a problem that we will not consider. But even if we pick a simple experimental set up, where the objects in the scene have few geometrical details, a graphics system will still have a hard time predicting the result of taking a picture with a digital camera. The problem here is to model the optical properties of the materials correctly. In this chapter, we show how Lorenz–Mie theory enables us to compute the optical properties of turbid materials such that we can predict their appearance. To describe the entire process of predicting the appearance of a material, we include a description of the mathematical models used in realistic image synthesis.