By Topic

Dimensional emotion driven facial expression synthesis based on the multi-stream DBN model

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
$33 $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)
Hao Wu ; VUB-NPU Joint Res. Group on AVSP, Northwestern Polytech. Univ., Xi'an, China ; Dongmei Jiang ; Yong Zhao ; Hichem Sahli

This paper proposes a dynamic Bayesian network (DBN) based MPEG-4 compliant 3D facial animation synthesis method driven by the (Evaluation, Activation) values in the continuous emotion space. For each emotion, a state synchronous DBN model (SS_DBN) is firstly trained using the Cohn-Kanade (CK) database with two streams of inputs: (i) the annotated (Evaluation, Activation) values, and (ii) the extracted Facial Action Parameters (FAPs) of the face image sequences. Then given an input (Evaluation, Activation) sequence, the optimal FAP sequence is estimated via the maximum likelihood estimation (MLE) criterion, and then used to construct the MPEG-4 compliant 3D facial animation. Compared with the state-of-the-art approaches where the mapping between the emotional space and the FAPs has been made empirically, in our approach the mapping is learned and optimized using DBN to fit the input (Evaluation, Activation) sequence. Emotion recognition results on the constructed facial animations, as well as subjective evaluations, show that the proposed method obtains natural facial animations representing well the dynamic process of the emotions from neutral to exaggerate.

Published in:

Signal & Information Processing Association Annual Summit and Conference (APSIPA ASC), 2012 Asia-Pacific

Date of Conference:

3-6 Dec. 2012