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Measurement and modeling of microfacet distributions under deformation
Abstract
We endeavor to model dynamic microfacet distributions of rough surfaces such as skin to simulate the changes in surface BRDF under stretching and compression. We begin by measuring microfacet distributions at 5-micron scale of several surface patches under controlled deformation. Generally speaking, rough surfaces become flatter and thus shinier as they are pulled tighter, and become rougher under compression. From this data, we build a model of how surface reflectance changes as the material deforms. We then simulate dynamic surface reflectance by modifying the anisotropic roughness parameters of a microfacet distribution model in accordance with animated surface deformations. Furthermore, we directly render such dynamic appearance by driving dynamic micro geometries to demonstrate how they influence the meso-scale surface reflectance.
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The surface of the skin is covered by intersecting grooves and ridges which produce characteristic skin surface patterns. It has been suggested that these folds provide a reserve of tissue, allowing the skin to stretch during normal function1–3. The extensibility of the skin depends on the direction of extension4, and the skin surface patterns are apparently also directionally disposed5. The relationship between the structural directionality of the surface and the directional extensibility of the skin was investigated in vivo.
Current scanning techniques record facial mesostructure with sub-millimeter precision showing pores, wrinkles, and creases. However, surface roughness continues to shape specular reflection at the level of microstructure: micron scale structures. Here, we present an approach to increase the resolution of mesostructure-level facial scans using microstructure examples digitized about the face. We digitize the skin patches using polarized gradient illumination and 10 μm resolution macro photography, and observe point-source reflectance measurements to characterize the specular reflectance lobe at this smaller scale. We then perform constrained texture synthesis to create appropriate surface microstructure per facial region, blending the regions to cover the whole entire face. We show that renderings of microstructure-augmented facial models preserve the original scanned mesostructure and exhibit surface reflections which are qualitatively more consistent with real photographs.