BioSpec: A Biophysically-Based Spectral Model of Light Interaction with Human Skin

Despite the notable progress in physically-based rendering, there is still a long way to go before we can automatically generate predictable images of biological materials. In this thesis, we address an open problem in this area, namely the spectral simulation of light interaction with human skin, and propose a novel biophysically-based model that accounts for all components of light propagation in skin tissues, namely surface reflectance, subsurface reflectance and transmittance, and the biological mechanisms of light absorption by pigments in these tissues. The model is controlled by biologically meaningful parameters, and its formulation, based on standard Monte Carlo techniques, enables its straightforward incorporation into realistic image synthesis frameworks. Besides its biophysicallybased nature, the key difference between the proposed model and the existing skin models is its comprehensiveness, i. e. , it computes both spectral (reflectance and transmittance) and scattering (bidirectional surface-scattering distribution function) quantities for skin specimens. In order to assess the predictability of our simulations, we evaluate their accuracy by comparing results from the model with actual skin measured data. We also present computer generated images to illustrate the flexibility of the proposed model with respect to variations in the biological input data, and its applicability not only in the predictive image synthesis of different skin tones, but also in the spectral simulation of medical conditions

An Introduction to Light Interaction with Human Skin

Despite the notable progress in physically-based rendering, there is still a long way to go before one can automatically generate predictable images of organic materials such as human skin. In this tutorial, the main physical and biological aspects involved in the processes of propagation and absorption of light by skin tissues are examined. These processes affect not only skin appearance, but also its health. For this reason, they have also been the object of study in biomedical research. The models of light interaction with human skin developed by the biomedical community are mainly aimed at the simulation of skin spectral properties which are used to determine the concentration and distribution of various substances. In computer graphics, the focus has been on the simulation of light scattering properties that affect skin appearance. Computer models used to simulate these spectral and scattering properties are described in this tutorial, and their strengths and limitations discussed. Keywords: natural phenomena, biologically and physically-based rendering

Hyperspectral Modeling of Material Appearance: General Framework, Challenges and Prospects

The main purpose of this tutorial is to address theoretical and practical issues involved in the development of predictive material appearancemodels for interdisciplinary applications within and outside the visible spectral domain. We examine the specific constraints and pitfalls found in each of the key stages of the model development framework, namely data collection, design and evaluation, and discuss alternatives to enhance the effectiveness of the entire process. Although predictive material appearance models developed by computer graphics researchers are usually aimed at realistic image synthesis applications, they also provide valuable support for a myriad of advanced investigations in related areas, such as computer vision, image processing and pattern recognition, which rely on the accurate analysis and interpretation of material appearance attributes in the hyperspectral domain. In fact, their scope of contributions goes beyond the realm of traditional computer science applications. For example, predictive light transport simulations, which are essential for the development of these models, are also regularly beingused by physical and life science researchers to understand andpredict material appearance changes prompted by mechanisms which cannot be fully studied using standard ``wet'' experimental procedures.For completeness, this tutorial also provides an overview of such synergistic research efforts and in silico investigations, which are illustrated by case studies involving the use of hyperspectral material appearance models

On the Modelling of Hyperspectral Light and Skin Interactions and the Simulation of Skin Appearance Changes Due to Tanning

The distinctive visual attributes of human skin are largely determined by its interactions with light across different spectral domains. Accordingly, the modelling of these interactions has been the object of extensive investigations in numerous fields for a diverse range of applications. However, only a relatively small portion of these research efforts has been directed toward the comprehensive simulation of hyperspectral light and skin interactions, as well as the associated temporal changes in skin appearance, which can be caused by a myriad of time-dependent photobiological phenomena. In this thesis, we explore this area of research. Initially, we present the first hyperspectral model designed for the predictive rendering of skin appearance attributes in the ultraviolet, visible and infrared domains. We then describe a novel physiologically-based framework for the simulation and visualization of skin tanning dynamics, arguably the most prominent and persistent of such relevant time-dependent phenomena. The proposed model incorporates the intrinsic bio-optical properties of human skin affecting hyperspectral light transport, including the particle nature and distribution patterns of the main light attenuation agents found within the cutaneous tissues. Accordingly, it accounts for phenomena that significantly affect skin spectral signatures within and outside the visible domain, such as detour and sieve effects, which are overlooked by existing skin appearance models. Using a first principles approach, this model computes the surface and subsurface scattering components of skin reflectance taking into account not only the wavelength and the illumination geometry, but also the positional dependence of the reflected light. Hence, the spectral and spatial distributions of light interacting with human skin can be comprehensively represented in terms of hyperspectral reflectance and scattering distribution functions respectively. The proposed tanning simulation framework incorporates algorithms that explicitly account for the connections between spectrally-dependent light stimuli and time-dependent physiological changes occurring within the cutaneous tissues. For example, it utilizes the above hyperspectral model as a modular component to evaluate the wavelength-dependence of the tanning phenomenon. This enables the effective simulation of the skin's main adaptive mechanisms to ultraviolet radiation as well as its responses to distinct light exposure regimes. We demonstrate the predictive capabilities of this framework through quantitative and qualitative comparisons of simulated data with measurements and experimental observations reported in the scientific literature. We also provide image sequences depicting skin appearance changes elicited by time-dependent variations in skin biophysical parameters. The work presented in this thesis is expected to contribute to advances in realistic image synthesis by increasing the spectral and temporal domains of material appearance modelling, and to provide a testbed for interdisciplinary investigations involving the visualization of skin responses to photoinduced processes

On the Modelling of Hyperspectral Light and Skin Interactions and the Simulation of Skin Appearance Changes Due to Tanning

The distinctive visual attributes of human skin are largely determined by its interactions with light across different spectral domains. Accordingly, the modelling of these interactions has been the object of extensive investigations in numerous fields for a diverse range of applications. However, only a relatively small portion of these research efforts has been directed toward the comprehensive simulation of hyperspectral light and skin interactions, as well as the associated temporal changes in skin appearance, which can be caused by a myriad of time-dependent photobiological phenomena. In this thesis, we explore this area of research. Initially, we present the first hyperspectral model designed for the predictive rendering of skin appearance attributes in the ultraviolet, visible and infrared domains. We then describe a novel physiologically-based framework for the simulation and visualization of skin tanning dynamics, arguably the most prominent and persistent of such relevant time-dependent phenomena. The proposed model incorporates the intrinsic bio-optical properties of human skin affecting hyperspectral light transport, including the particle nature and distribution patterns of the main light attenuation agents found within the cutaneous tissues. Accordingly, it accounts for phenomena that significantly affect skin spectral signatures within and outside the visible domain, such as detour and sieve effects, which are overlooked by existing skin appearance models. Using a first principles approach, this model computes the surface and subsurface scattering components of skin reflectance taking into account not only the wavelength and the illumination geometry, but also the positional dependence of the reflected light. Hence, the spectral and spatial distributions of light interacting with human skin can be comprehensively represented in terms of hyperspectral reflectance and scattering distribution functions respectively. The proposed tanning simulation framework incorporates algorithms that explicitly account for the connections between spectrally-dependent light stimuli and time-dependent physiological changes occurring within the cutaneous tissues. For example, it utilizes the above hyperspectral model as a modular component to evaluate the wavelength-dependence of the tanning phenomenon. This enables the effective simulation of the skin's main adaptive mechanisms to ultraviolet radiation as well as its responses to distinct light exposure regimes. We demonstrate the predictive capabilities of this framework through quantitative and qualitative comparisons of simulated data with measurements and experimental observations reported in the scientific literature. We also provide image sequences depicting skin appearance changes elicited by time-dependent variations in skin biophysical parameters. The work presented in this thesis is expected to contribute to advances in realistic image synthesis by increasing the spectral and temporal domains of material appearance modelling, and to provide a testbed for interdisciplinary investigations involving the visualization of skin responses to photoinduced processes

A Study on Skin Optics

Despite the notable progress in physically-based rendering, there is still a long way to go before we can automatically generate predictable images of biological materials. In this report, we address an open problem in this area, namely the spectral simulation of light interaction with human skin. Initially, we present an overview of fundamental skin optics concepts which is followed by the description of a novel biophysically-based model that accounts for all components of light propagation in skin tissues, namely surface reflectance, subsurface reflectance and transmittance, and the biological mechanisms of light absorption by pigments in these tissues. The model is controlled by biologically meaningful parameters, and its formulation, based on standard Monte Carlo techniques, enables its straightforward incorporation into realistic image synthesis frameworks. Besides its biophysically-based nature, the key difference between the proposed model and the existing skin models is its comprehensiveness, i.e., it computes both spectral (reflectance and transmittance) and scattering (bidirectional surface-scattering distribution function) quantities for skin specimens. In order to assess the predictability of our simulations, we evaluate their accuracy by comparing results from the model with actual skin measured data. We also present computer generated images to illustrate the flexibility of the proposed model with respect to variations in the biological input data, and its applicability not only in the predictive image synthesis of different skin tones, but also in the spectral simulation of medical conditions.