Low Bandwidth Video Streaming using FACS, Facial Expression and Animation Techniques

Dinesh Kumar, Jito Vanualailai

Abstract

In this paper we describe an easy to use real-time 3D facial expression and animation system that takes the creation of individual facial expressions to the atomic level. That is instead of generating and recording known facial expressions we propose a mechanism that will allow us to create and store each atomic facial distortion. We can then combine some of these singular distortions to create meaningful expressions. FACS Action Units (AUs) is one such technique that describes the simplest visible movement, which cannot be decomposed into more basic ones. We use this as the basis for creating these atomic facial distortions. The Waters muscle based facial model has been used and extended to allow the user to calibrate and record each facial deformation as described in FACS AUs. The user can then create any facial expression by simply stating the series of AUs and its degree of activation in a controlled fashion. These features all form part of the Facial Animation System (FAS). Our FAS is implemented in such a way that enables it to be used as a low bandwidth video streaming player - a real time facial animation player driven only by FACS AUs transmitted as plain text over TCP sockets.

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Paper Citation


in Harvard Style

Kumar D. and Vanualailai J. (2016). Low Bandwidth Video Streaming using FACS, Facial Expression and Animation Techniques . In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2016) ISBN 978-989-758-175-5, pages 226-235. DOI: 10.5220/0005718202240233


in Bibtex Style

@conference{grapp16,
author={Dinesh Kumar and Jito Vanualailai},
title={Low Bandwidth Video Streaming using FACS, Facial Expression and Animation Techniques},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2016)},
year={2016},
pages={226-235},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005718202240233},
isbn={978-989-758-175-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2016)
TI - Low Bandwidth Video Streaming using FACS, Facial Expression and Animation Techniques
SN - 978-989-758-175-5
AU - Kumar D.
AU - Vanualailai J.
PY - 2016
SP - 226
EP - 235
DO - 10.5220/0005718202240233