Facial Auto Rigging from 4D Expressions via Skinning Decomposition

Zhihe Zhao, Dongdong Weng*, Hanzhi Guo, Jing Hou, Jixiang Zhou

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

1 引用 (Scopus)

摘要

This paper proposes a framework that utilizes skinning decomposition to automatically generate facial rigging from 4D expressions. The framework inputs a predefined rigging template and an actor's 4D facial expressions, including a neutral expression, as well as a group of arbitrary expressions. The output includes not only the linear blend skinning weights and joint positions of the actor's head mesh but also other facial components such as teeth and eyes. Compared to traditional methods, this paper applies a soft constraint to optimize joint positions and imposes a fixed sparsity distribution constraint to improve weight distribution. To further enhance rigging efficiency, this paper leverages GPU expression-parallel and CPU vertex-parallel strategies for joint transformation and weight updates, respectively. The experiments show that the proposed method generates high-fidelity facial rigging that outperforms existing solutions in terms of computational speed, joint position correctness, weight distribution correctness, or computational cost.

源语言英语
主期刊名MM 2023 - Proceedings of the 31st ACM International Conference on Multimedia
出版商Association for Computing Machinery, Inc
6101-6109
页数9
ISBN(电子版)9798400701085
DOI
出版状态已出版 - 26 10月 2023
活动31st ACM International Conference on Multimedia, MM 2023 - Ottawa, 加拿大
期限: 29 10月 20233 11月 2023

出版系列

姓名MM 2023 - Proceedings of the 31st ACM International Conference on Multimedia

会议

会议31st ACM International Conference on Multimedia, MM 2023
国家/地区加拿大
Ottawa
时期29/10/233/11/23

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