Scheduled System Maintenance:
On Monday, April 27th, IEEE Xplore will undergo scheduled maintenance from 1:00 PM - 3:00 PM ET (17:00 - 19:00 UTC). No interruption in service is anticipated.
By Topic

Real-time speech-driven 3D face animation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Hong, Pengyu ; Coordinated Sci. Lab., Illinois Univ., Urbana, IL, USA ; Zhen Wen ; Huang, T.S. ; Heung-Yeung Shum

In this paper, we present an approach for real-time speech-driven 3D face animation using neural networks. We first analyze a 3D facial movement sequence of a talking subject and learn a quantitative representation of the facial deformations, called the 3D motion units (MUs). A 3D facial deformation can be approximated by a linear combination of the MUs weighted by the MU parameters (MUPs) - the visual features of the facial deformation. The facial movement sequence synchronizes with a audio track. The audio track is digitized and the audio features of each frame are calculated. A real-time audio-to-MUP mapping is constructed by training a set of neural networks using the calculated audio-visual features. The audio-visual features are divided into several groups based on the audio features. One neural network is trained per group to map the audio features to the corresponding MUPs. Given a new audio feature vector, we first classify it into one of the groups and select the corresponding neural network to map the audio feature vector to MUPs, which are used for face animation. The quantitative evaluation shows the effectiveness of the proposed approach.

Published in:

3D Data Processing Visualization and Transmission, 2002. Proceedings. First International Symposium on

Date of Conference: