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Measuring facial expressions by computer image analysis

Published online by Cambridge University Press:  01 March 1999

MARIAN STEWART BARTLETT
Affiliation:
Departments of Cognitive Science and Psychology, University of California, San Diego, USA The Salk Institute, Computational Neurobiology Laboratory, La Jolla, CA, USA
JOSEPH C. HAGER
Affiliation:
Network Information Research Corp., Salt Lake City, UT, USA
PAUL EKMAN
Affiliation:
Department of Psychiatry, University of California, San Francisco, USA
TERRENCE J. SEJNOWSKI
Affiliation:
Department of Biology, University of California, San Diego, USA Howard Hughes Medical Institute, The Salk Institute, Computational Neurobiology Laboratory, La Jolla, CA, USA
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Abstract

Facial expressions provide an important behavioral measure for the study of emotion, cognitive processes, and social interaction. The Facial Action Coding System (Ekman & Friesen, 1978) is an objective method for quantifying facial movement in terms of component actions. We applied computer image analysis to the problem of automatically detecting facial actions in sequences of images. Three approaches were compared: holistic spatial analysis, explicit measurement of features such as wrinkles, and estimation of motion flow fields. The three methods were combined in a hybrid system that classified six upper facial actions with 91% accuracy. The hybrid system outperformed human nonexperts on this task and performed as well as highly trained experts. An automated system would make facial expression measurement more widely accessible as a research tool in behavioral science and investigations of the neural substrates of emotion.

Type
Research Article
Copyright
1999 Society for Psychophysiological Research

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