A Self-Shadow Algorithm for Dynamic Hair using Density Clustering

Abstract

Self-shadowing is an important factor in the appearance of hair and fur. In this paper we present a new rendering algorithm to accurately compute shadowed hair at interactive rates using graphics hardware. No constraint is imposed on the hair style, and its geometry can be dynamic. Similar to previously presented methods, a 1D visibility function is constructed for each line of sight of the light source view. Our approach differs from other work by treating the hair geometry as a 3D density field, which is sampled on the fly using simple rasterization. The rasterized fragments are clustered, effectively estimating the density of hair along a ray. Based hereon, the visibility function is constructed. We show that realistic selfshadowing of thousands of individual dynamic hair strands can be rendered at interactive rates using consumer graphics hardware.