Realistic visualization of cloth has many applications in computer graphics. An ongoing research problem is how to best represent and capture cloth models, specifically when considering computer aided design of cloth. Previous methods produce highly realistic images, however, they are either difficult to edit or require the measurement of large databases to capture all variations of a cloth sample. We propose a pipeline to reverse engineer cloth and estimate a parametrized cloth model from a single image. We introduce a geometric yarn model, integrating state-of-the-art textile research. We present an automatic analysis approach to estimate yarn paths, yarn widths, their variation and a weave pattern. Several examples demonstrate that we are able to model the appearance of the original cloth sample. Properties derived from the input image give a physically plausible basis that is fully editable using a few intuitive parameters.

Abstract Visual prototyping of materials is relevant for many computer graphics applications. A large amount of modelling flexibility can be obtained by directly rendering micro‐geometry. While this is possible in principle, it is usually computationally expensive. Recently, bidirectional texture functions (BTFs) have become popular for efficient photorealistic rendering of surfaces. We propose an efficient system for the computation of synthetic BTFs using Monte Carlo path tracing of micro‐geometry. We observe that BTFs usually consist of many similar apparent bidirectional reflectance distribution functions. By exploiting structural similarity we can reduce rendering times by one order of magnitude. This is done in a process we call non‐local image reconstruction, which has been inspired by non‐local means filtering. Our results indicate that synthesizing BTFs is highly practical and may currently only take a few minutes for BTFs with 70 × 70 viewing and lighting directions and 128 × 128 pixels.

This course is about recent advances in the challenging field of physically-based appearance modeling of cloth. Apart from geometrical complexity, optical complexity presents complications as highly anisotropic single and multiple scattering effects often dominate the appearance. Many types of fibers are highly translucent and multiple scattering significantly influences the observed color. Since a cloth model may potentially consist of billions of fibers, finding a viable level of geometrical abstraction is difficult. After explaining the general structure of several types of textiles, we give an overview of different approaches that have been proposed to render cloth. As the micro-geometry of cloth can be represented using an explicit representation of a fiber assembly, we continue by explaining optical properties of fibers; these can be derived from first principles of physics such as absorption or index of refraction. Understanding light scattering from fibers is essential, when a physically-based cloth renderer is designed. However, as storing these fibers explicitly is often too costly, more efficient statistical descriptions of cloth have also been proposed that can be used together with volumetric rendering techniques to allow for physically-based image synthesis, while retaining most of the flexibility of explicit methods. A major part of this course will focus on these approaches. We discuss the theory and practice of physically-based rendering of anisotropic media. The discussion begins with a review of linear transport theory, upon which current methods for rendering volumetric cloth are based. Relevant implementation details are discussed at each stage, and the final result will be the pseudocode of a Monte Carlo path tracer for volumetric cloth representations. Although rendering of cloth is a very specialized task, many of the concepts, developed in this field, can be used for rendering other materials with complex micro-geometry as well.

Virtual reproduction of optical material properties is an important task for many computer graphics applications. Recently, bidirectional texture functions (BTFs) [Dana et al. 1999] have become quite popular for photo-realistic rendering of surfaces. BTFs can represent a huge variety of different materials. They can be easily integrated into any modern rendering system which offers programmable surface shaders. BTFs of real materials can be optically measured, they are known to be efficiently compressible and can be used for real-time graphics rendering applications even on the web using WebGL.

Abstract Efficient physically accurate modeling and rendering of woven cloth at a yarn level is an inherently complicated task due to the underlying geometrical and optical complexity. In this paper, a novel and general approach to physically accurate cloth rendering is presented. By using a statistical volumetric model approximating the distribution of yarn fibers, a prohibitively costly explicit geometrical representation is avoided. As a result, accurate rendering of even large pieces of fabrics containing orders of magnitudes more fibers becomes practical without sacrifying much generality compared to fiber‐based techniques. By employing the concept of local visibility and introducing the effective fiber density, limitations of existing volumetric approaches regarding self‐shadowing and fiber density estimation are greatly reduced.