Chain Shape Matching for Simulating Complex Hairstyles

Abstract

Animations of hair dynamics greatly enrich the visual attractiveness of human characters. Traditional simulation techniques handle hair as clumps or continuum for efficiency; however, the visual quality is limited because they cannot represent the fine-scale motion of individual hair strands. Although a recent mass-spring approach tackled the problem of simulating the dynamics of every strand of hair, it required a complicated setting of springs and suffered from high computational cost. In this paper, we base the animation of hair on such a fine-scale on Lattice Shape Matching (LSM), which has been successfully used for simulating deformable objects. Our method regards each strand of hair as a chain of particles, and computes geometrically derived forces for the chain based on shape matching. Each chain of particles is simulated as an individual strand of hair. Our method can easily handle complex hairstyles such as curly or afro styles in a numerically stable way. While our method is not physically based, our GPU-based simulator achieves visually plausible animations consisting of several tens of thousands of hair strands at interactive rates