Predictive Modeling of Material Appearance: From the Drawing Board to Interdisciplinary Applications

Abstract

This tutorial addresses one of the fundamental and timely topics of computer graphics research, namely the predictive modeling of material appearance. Although this topic is deeply rooted in traditional areas like rendering and natural phenomena simulation, this tutorial is not limited to cover contents connected to these areas. It also closely looks into the scientific methodology employed in the development of predictive models of light and matter interactions. Given the widespread use of this methodology to find modeling solutions for problems within and outside computer graphics, its discussion from a ''behind the scenes'' perspective aims to underscore practical and far-reaching aspects of interdisciplinary research that are often overlooked in related publications. More specifically, this tutorial unveils constraints and pitfalls found in each of the key stages of the model development process, namely data collection, design and evaluation, and brings forward alternatives to tackle them effectively. Furthermore, besides being a central component of realistic image synthesis frameworks, predictive material appearance models have a scope of applications that can be extended far beyond the generation of believable images. For instance, they can be employed to accelerate the hypothesis generation and validation cycles of research across a wide range of fields, from biology and medicine to photonics and remote sensing, among others. These models can also be used to generate comprehensive in silico (computational) datasets to support the translation of knowledge advances in those fields to real-world applications (e.g., the noninvasive screening of medical conditions and the remote detection of environmental hazards). In fact, a number of them are already being used in physical and life sciences, notably to support investigations seeking to strengthen the current understanding about material appearance changes prompted by mechanisms which cannot be fully studied using standard ''wet'' experimental procedures. Accordingly, such interdisciplinary research initiatives are also discussed in this tutorial through selected case studies involving the use of predictive material appearance models to elucidate challenging scientific questions.