Building volumetric appearance models of fabric using micro CT imaging

Abstract

Figure 1: We build volumetric appearance models of complex materials like velvet using CT imaging: (left) CT data gives scalar density over a small volume; (center) we extract fiber orientation (shown in false color) and tile larger surfaces; and (right) we match appearance parameters to photographs to create a complete appearance model. Both fine detail and the characteristic highlights of velvet are reproduced. AbstractThe appearance of complex, thick materials like textiles is determined by their 3D structure, and they are incompletely described by surface reflection models alone. While volume scattering can produce highly realistic images of such materials, creating the required volume density models is difficult. Procedural approaches require significant programmer effort and intuition to design specialpurpose algorithms for each material. Further, the resulting models lack the visual complexity of real materials with their naturallyarising irregularities. This paper proposes a new approach to acquiring volume models, based on density data from X-ray computed tomography (CT) scans and appearance data from photographs under uncontrolled illumination. To model a material, a CT scan is made, resulting in a scalar density volume. This 3D data is processed to extract orientation information and remove noise. The resulting density and orientation fields are used in an appearance matching procedure to define scattering properties in the volume that, when rendered, produce images with texture statistics that match the photographs. As our results show, this approach can easily produce volume appearance models with extreme detail, and at larger scales the distinctive textures and highlights of a range of very different fabrics like satin and velvet emerge automatically-all based simply on having accurate mesoscale geometry.

Fitting procedural yarn models for realistic cloth rendering

“…Although these models provide high-quality renderings for fabrics viewed from a distance, they lack the power to closely reproduce the appearance of fabrics with thick yarns or fuzzy silhouettes, or the generality to handle different fabrics with wildly varying appearances. Recent advances in cloth appearance modeling have led to the development of volumetric [Xu et al 2001;Jakob et al 2010;Zhao et al 2011;Zhao et al 2012;Zhao et al 2013] and fiber-based [Schröder et al 2015;Khungurn et al 2015] cloth models. Unlike traditional methods, they describe fabrics at 3D volumes with varying densities (volumetric) or collections of fiber curves (fiber-based).…”

“…Compared to traditional surface-based methods, these models are better at capturing the thickness and fuzziness of fabrics, which add significantly to their visual realism, and thus have brought the quality of computed rendered cloth to the next level. However, these techniques either provide automated creation of highly realistic models (achieved by measuring real-world samples) but carry little highlevel synthetic information (e.g., yarn twisting) [Zhao et al 2011;Khungurn et al 2015], or offer compact procedural representations but rely on manually configured models which require nontrivial parameter tweaking to match reality closely [Schröder et al 2015].…”

“…The geometric structure of fabrics have been studied by the textile research community for decades. State-of-theart results from this field [Morris et al 1999;Tao 1996;Keefe 1994;Shinohara et al 2010] have resulted in the introduction of some aforementioned micro-appearance modeling techniques [Zhao et al 2011;Schröder et al 2015].…”

“…SIGGRAPH '16 Technical Paper, July 24 -28, 2016, Anaheim, CA, ISBN: 978-1-4503-4279-7/16/07 DOI: http://dx.doi.org/10.1145 Representing the richness of fabrics in virtual models has actively driven research in a variety of fabric appearance models. Recently, micro-appearance based fabric models [Zhao et al 2011;Zhao et al 2012;Khungurn et al 2015;Schröder et al 2015] that explicitly capture a fabric's micro-scale geometry have been introduced. Compared to traditional methods, these models describe fabrics at unprecedented detail, and thus offer superior generality as the complex appearance of a fabric is largely a direct consequence of its small-scale structures.…”

“…Previously, these detailed structures were measured through volume imaging (e.g., computed microtomography), leading to high-resolution 3D volumes [Zhao et al 2011;Zhao et al 2012] or large numbers of unorganized fiber curves [Khungurn et al 2015]. Neither of these representations is easy to manipulate.…”