A Stationary SVBRDF Material Modeling Method Based on Discrete Microsurface

Abstract

Microfacet theory is commonly used to build reflectance models for surfaces. While traditional microfacet-based models assume that the distribution of a surface's microstructure is continuous, recent studies indicate that some surfaces with tiny, discrete and stochastic facets exhibit glittering visual effects, while some surfaces with structured features exhibit anisotropic specular reflection. Accordingly, this paper proposes an efficient and stationary method of surface material modeling to process both glittery and non-glittery surfaces in a consistent way. Our method comprises two steps: in the preprocessing step, we take a fixed-size sample normal map as input, then organize 4D microfacet trees in position and normal space for arbitrary-sized surfaces; we also cluster microfacets into 4D K-lobes via the adaptive k-means method. In the rendering step, moreover, surface normals can be efficiently evaluated using pre-clustered microfacets. Our method is able to efficiently render any structured, discrete and continuous micro-surfaces using a precisely reconstructed surface NDF. Our method is both faster and uses less memory compared to the state-of-the-art glittery surface modeling works.