An adaptive floating tangents fitting with helices method for image-based hair modeling
PubDate: June 201
Teams: Beihang University
Writers: Yongtang Bao；Yue Qi
Currently, hair geometry is mostly represented as sequences of 3D points. It is difficult to simulate hair directly from this representation. This paper proposes a novel approach to convert hair geometry model into helices, which could be easily plugged into dynamic hair simulation. We construct a hair model from a hybrid orientation field. Then we use adaptive floating tangents fitting algorithm to convert this hair geometry model into a physics-based hair model. We simulate dynamic hair by Lagrange equations. Results show that this approach can preserve structural details of 3D hair models, and can be applied to simulate various hair geometries.