By Topic

Automated facial expression recognition based on FACS action units

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)
Lien, J.J. ; Dept. of Electr. Eng., Pittsburgh Univ., PA, USA ; Kanade, T. ; Cohn, J.F. ; Li, C.-C.

Automated recognition of facial expression is an important addition to computer vision research because of its relevance to the study of psychological phenomena and the development of human-computer interaction (HCI). We developed a computer vision system that automatically recognizes individual action units or action unit combinations in the upper face using hidden Markov models (HMMs). Our approach to facial expression recognition is based an the Facial Action Coding System (FACS), which separates expressions into upper and lower face action. We use three approaches to extract facial expression information: (1) facial feature point tracking; (2) dense flow tracking with principal component analysis (PCA); and (3) high gradient component detection (i.e. furrow detection). The recognition results of the upper face expressions using feature point tracking, dense flow tracking, and high gradient component detection are 85%, 93% and 85%, respectively

Published in:

Automatic Face and Gesture Recognition, 1998. Proceedings. Third IEEE International Conference on

Date of Conference:

14-16 Apr 1998