Shape Adaptation for 3D Hairstyle Retargeting

TL;DR

This paper introduces an automatic, multi-scale shape adaptation method for retargeting 3D hairstyles onto different characters, combining optimization, local detail refinement, and user customization tools.

Contribution

It presents a novel multi-scale optimization framework for hairstyle retargeting and a physics-based hairline editing tool for user customization.

Findings

Effective retargeting of diverse hairstyles demonstrated

Multi-scale approach improves computational efficiency

User customization via hairline editing enhances flexibility

Abstract

It is demanding to author an existing hairstyle for novel characters in games and VR applications. However, it is a non-trivial task for artists due to the complicated hair geometries and spatial interactions to preserve. In this paper, we present an automatic shape adaptation method to retarget 3D hairstyles. We formulate the adaptation process as a constrained optimization problem, where all the shape properties and spatial relationships are converted into individual objectives and constraints. To make such an optimization on high-resolution hairstyles tractable, we adopt a multi-scale strategy to compute the target positions of the hair strands in a coarse-to-fine manner. The global solving for the inter-strands coupling is restricted to the coarse level, and the solving for fine details is made local and parallel. In addition, we present a novel hairline edit tool to allow for user customization during retargeting. We achieve it by solving physics-based deformations of an embedded membrane to redistribute the hair roots with minimal distortion. We demonstrate the efficacy of our method through quantitative and qualitative experiments on various hairstyles and characters.