Physically Based Modeling of Micro-Appearance

Abstract

This dissertation addresses the challenges of creating photorealistic images by focusing on generating and rendering microscale details and irregularities, because a lack of such imperfections is usually the key aspect of telling a photograph from a synthetic, computer-generated image. <br /> In Chapter 3, we model the fluid flow on soap bubbles, which demonstrate iridescent beauty due to their micrometer-scale thickness. Instead of approximating the variation in film thickness with random noise textures, this work incorporates the underlying mechanics that drive such fluid flow, namely the Navier-Stokes equations, which include factors such as surfactant concentration, Marangoni surface tension, and evaporation. We address challenges such as the singularity at poles in spherical coordinates and the need for extremely small step sizes in a stiff system to simulate a wide range of dynamic effects. As a result, our approach produces soap bubble renderings that match real-world footage. <br /> Chapter 4 explores hair rendering. Existing models based on the Marschner model split the scattering function into a longitudinal and an azimuthal component. While this separation benefits importance sampling, it lacks a physical ground and does not match measurements. We propose a novel physically based hair scattering model, representing hair as cylinders with microfacet roughness. We reveal that the focused highlight in the forward-scattering direction observed in the measurement is a result of the rough cylindrical geometry itself. Additionally, our model naturally extends to elliptical hair fibers. <br /> A much related topic, feather rendering, is discussed in Chapter 5. Unlike human hairs, feathers possess unique substructures, such as barbs and barbules with irregular cross-sections, the existing pipeline of modeling feathers using hair shaders therefore fails to accurately describe their appearance. We propose a model that directly accounts for these multi-scale geometries by representing feathers as collections of barb primitives and incorporating the contributions of barbule cross-sections using a normal distribution function. We demonstrate the effectiveness of our model on rock dove neck feathers, showing close alignment with measurements and photographs.