Enhanced Waters 2D Muscle Model for Facial Expression Generation

Dinesh Kumar, Dharmendra Sharma

2019

Abstract

In this paper we present an improved Waters facial model used as an avatar for work published in (Kumar and Vanualailai, 2016), which described a Facial Animation System driven by the Facial Action Coding System (FACS) in a low-bandwidth video streaming setting. FACS defines 32 single Action Units (AUs) which are generated by an underlying muscle action that interact in different ways to create facial expressions. Because FACS AU describes atomic facial distortions using facial muscles, a face model that can allow AU mappings to be applied directly on the respective muscles is desirable. Hence for this task we choose the Waters anatomy-based face model due to its simplicity and implementation of pseudo muscles. However Waters face model is limited in its ability to create realistic expressions mainly the lack of a function to represent sheet muscles, unrealistic jaw rotation function and improper implementation of sphincter muscles. Therefore in this work we provide enhancements to the Waters facial model by improving its UI, adding sheet muscles, providing an alternative implementation to the jaw rotation function, presenting a new sphincter muscle model that can be used around the eyes and changes to operation of the sphincter muscle used around the mouth.

Paper Citation

in Harvard Style

Kumar D. and Sharma D. (2019). Enhanced Waters 2D Muscle Model for Facial Expression Generation. In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 1: GRAPP; ISBN 978-989-758-354-4, SciTePress, pages 262-269. DOI: 10.5220/0007379302620269

in Bibtex Style

@conference{grapp19,
author={Dinesh Kumar and Dharmendra Sharma},
title={Enhanced Waters 2D Muscle Model for Facial Expression Generation},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 1: GRAPP},
year={2019},
pages={262-269},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007379302620269},
isbn={978-989-758-354-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 1: GRAPP
TI - Enhanced Waters 2D Muscle Model for Facial Expression Generation
SN - 978-989-758-354-4
AU - Kumar D.
AU - Sharma D.
PY - 2019
SP - 262
EP - 269
DO - 10.5220/0007379302620269
PB - SciTePress