Recognizing Upper Face Action Units for Facial Expression Analysis

We develop an automatic system to analyze subtle changes in upper face expressions based on both permanent facial features (brows, eyes, mouth)andtransient facial features (deepening of facial furrows) in a nearly frontal image sequence. Our system recognizes fine-grained changes in facial expression based on Facial Action Coding System (FACS) action units (AUs). Multi-state facial component models are proposed for tracking and modeling different facial features, including eyes, brows, cheeks, and furrows. Then we convert the results of tracking to detailed parametric descriptions of the facial features. These feature parameters are fed to a neural network which recognizes 7 upper face action units. A recognition rate of 95% is obtained for the test data that include both single action units and AU combinations.

• Type: Conference
• Year: 2000
• Where: CVPR
• Authors: Ying-li Tian, Takeo Kanade, Jeffrey F. Cohn
• Keywords: Computer Vision, CVPR 2000, Facial Action, Facial Features, Facial Furrows, Multi-state Facial Component, Permanent Facial Features