Adaptive Skinning for Interactive Hair-Solid Simulation

Menglei Chai, Changxi Zheng and Kun Zhou

Reduced hair models have proven successful for interactively simulating a full head of hair strands, building upon a fundamental assumption that only a small set of guide hairs are needed for explicit simulation, and the rest of the hair move coherently and thus can be interpolated using guide hairs. Unfortunately, hair-solid interactions is a pathological case for traditional reduced hair models, as the motion coherence between hair strands can be arbitrarily broken by interacting with solids. In this paper, we propose an adaptive hair skinning method for interactive hair simulation with hair-solid collisions. We precompute many eligible sets of guide hairs and the corresponding interpolation relationships that are represented using a compact strand-based hair skinning model. At runtime, we simulate only guide hairs; for interpolating every other hair, we adaptively choose its guide hairs, taking into account motion coherence and potential hair-solid collisions. Further, we introduce a two-way collision correction algorithm to allow sparsely sampled guide hairs to resolve collisions with solids that can have small geometric features. Our method enables interactive simulation of more than 150K hair strands interacting with complex solid objects, using 400 guide hairs. We demonstrate the efficiency and robustness of the method with various hairstyles and user-controlled arbitrary hair-solid interactions.

Adaptive Skinning for Interactive Hair-Solid Simulation

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