Towards Realtime: A Hybrid Physics-based Method for Hair Animation on GPU (Best Paper Honorable Mentions)
Authors
Li Huang, Fan Yang, Chendi Wei, Yu Ju (Edwin) Chen, Chun Yuan, and Ming Gao
Paper [PDF, 58MB] Best Paper Honorable Mentions
PowerPoint Slides(Available upon request)
Abstract
This paper introduces a hair simulator optimized for real-time applications, including console and cloud gaming, avatar live-streaming, and metaverse environments. We view the collisions between strands as a mechanism to preserve the overall volume of the hair and adopt explicit Material Point Method (MPM) to resolve the strand-strand collision. For simulating single-strand behavior, a semi-implicit Discrete Elastic Rods (DER) model is used. We build upon a highly efficient GPU MPM framework recently presented by Fei et al. [2021b] and propose several schemes to largely improve the performance of building and solving the semi-implicit DER systems on GPU. We demonstrate the efficiency of our pipeline by a few practical scenes that achieve up to 260 frames-per-second (FPS) with more than two thousand simulated strands on Nvidia GeForce RTX 3080.
Citation
@article{10.1145/3606937,
author = {Huang, Li and Yang, Fan and Wei, Chendi and Chen, Yu Ju (Edwin) and Yuan, Chun and Gao, Ming},
title = {Towards Realtime: A Hybrid Physics-Based Method for Hair Animation on GPU},
year = {2023},
issue_date = {August 2023},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
volume = {6},
number = {3},
url = {https://doi.org/10.1145/3606937},
doi = {10.1145/3606937},
abstract = {This paper introduces a hair simulator optimized for real-time applications, including console and cloud gaming, avatar live-streaming, and metaverse environments. We view the collisions between strands as a mechanism to preserve the overall volume of the hair and adopt explicit Material Point Method (MPM) to resolve the strand-strand collision. For simulating single-strand behavior, a semi-implicit Discrete Elastic Rods (DER) model is used. We build upon a highly efficient GPU MPM framework recently presented by Fei et al. [2021b] and propose several schemes to largely improve the performance of building and solving the semi-implicit DER systems on GPU. We demonstrate the efficiency of our pipeline by a few practical scenes that achieve up to 260 frames-per-second (FPS) with more than two thousand simulated strands on Nvidia GeForce RTX 3080.},
journal = {Proc. ACM Comput. Graph. Interact. Tech.},
month = {aug},
articleno = {43},
numpages = {18},
keywords = {hair, material point method, GPU}
}