Facial action coding system

By Paul Ekman, Wallace V. Friesen. 2019

564 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/7518aca48e6b8cd2257c98b64ed7ee3db69c0c1a

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In Computer Vision and Pattern Recognition

Citations in the corpus

Automatic Analysis of Facial Actions: A Survey (2019, methodology): “Co-occurring AUs can be additive, in which the appearance changes of each separate AU are relatively independent, or non-additive, in which one action masks another or a new and distinctive set of appearances is created [57].”
Engagement detection in online learning: a review (2019, background): “The FACS uses facial muscle movements also known as action units (AUs) in order to design the theoretical measure of specific discrete emotions (Ekman and Friesen 1978; Ekman et al. 2002).”
Interpreting CNN Models for Apparent Personality Trait Regression (2017, methodology): “4 to also predict a subset of 17 Action Units (AUs) from the Facial Action Coding System (FACS) [7] (namely: AU1-Inner brow raiser, AU2-Outer brow raiser, AU4-Brow lowerer , AU5-Upper lid raiser, AU6-Cheek raiser, AU7-Lid tightener, AU9-Nose wrinkler, AU10-Upper lip raiser, AU12-Lip corner puller, A”
AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wild (2017, methodology): “ment of Electrical and Computer Engineering, University of Denver, Denver, CO, 80210. E-mail: amollah, bhasani, mmahoor@du.edu all possible facial actions are described in terms of Action Units (AUs) [4]. FACS model explains facial movements and does not describe the affective state directly. There ”
paGAN (2018, unknown): “This sparse set can then be separated into a comprehensive set of blendshape-driven UV texture maps based on the Facial Action Coding System (FACS)[Ekman and Friesen 1978].”