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1998
IEEE

Automated Facial Expression Recognition Based on FACS Action Units

10 years 2 months ago
Automated Facial Expression Recognition Based on FACS Action Units
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 on the Facial Action Coding System (FACS), which separates expressions into upper and lower face action. In this paper, 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.
James Jenn-Jier Lien, Takeo Kanade, Jeffrey F. Coh
Added 04 Aug 2010
Updated 04 Aug 2010
Type Conference
Year 1998
Where FGR
Authors James Jenn-Jier Lien, Takeo Kanade, Jeffrey F. Cohn, Ching-Chung Li
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