September 2011
Volume 11, Issue 11
Vision Sciences Society Annual Meeting Abstract  |   September 2011
Facial Expression Production and Training
Author Affiliations
  • Iris Gordon
    Psychology, University of Victoria, USA
  • James W. Tanaka
    Psychology, University of Victoria, USA
  • Matt Pierce
    Psychology, University of Victoria, USA
  • Marian Bartlett
    Psychology, University of California at San Diego, USA
Journal of Vision September 2011, Vol.11, 565. doi:
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      Iris Gordon, James W. Tanaka, Matt Pierce, Marian Bartlett; Facial Expression Production and Training. Journal of Vision 2011;11(11):565.

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      © ARVO (1962-2015); The Authors (2016-present)

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Research in facial expression production has shown that typical adults are adept at performing facial expressions spontaneously, but not voluntarily. The current study investigates the effects of training on facial expression production in typical individuals using the Computer Emotion Recognition Toolbox (CERT) (Bartlett, 2006). CERT is a video processing program that detects frontal-faces in a live video stream, and codes each frame with respect to 40 dimensions, including the 6 basic emotions and 30 facial action units (AU's) from the Facial Action Coding System (FACS) (Ekman & Friesen, 1978). FaceMaze is an interactive Pac-man-like game in which players navigate though a maze overcoming obstacles by producing facial expressions based on feedback from CERT. Experiment 1 consisted of two blocks, targeting Happy and Angry expression production exclusively. Participants were given a pre-training assessment in which emotion words were presented and participants were required to perform the matching facial expression. Electromyography (EMG) measures were recorded from the Zygomaticus Major (ZM), the Currogator supercili (CS) and the Obicularis Occuli (OO) corresponding to the Happy, Angry and Surprise (control) expressions. Participants then played the FaceMaze game, followed by a post-training assessment that was identical to the pre-training assessment. Results revealed an improvement in expression production as indicated by post-FaceMaze increases in ZM and CS in the Happy and Angry block, respectively. In Experiment 2, naive participants were presented with videos of pre- and post-FaceMaze facial expressions and were asked to rate the video on the quality of the expression. Results showed that participants rated post-FaceMaze productions of the trained target expression reliably higher than pre-FaceMaze productions. In summary, the EMG findings from Experiment 1 and the expressions ratings from Experiment 2 support the use of CERT as a research and training tool in expression production and recognition.

This research was funded by grants from the James S. McDonnell Foundation, the National Science Foundation (#SBE-0542013), and the National Sciences and Engineering Research Council of Canada. 

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