KEYNOTE SPEAKER
Prof. Dr. Jeffrey F. Cohn
(Division of Psychology,
University of Pittsburgh, Pittsburh, PA, U.S.A.
and the Robotics Institute,
Carnegie Mellon University, Pittsburgh, PA, U.S.A.)
About the speaker
Jeffrey Cohn is Professor
of Psychology at the University of Pittsburgh and Adjunct Faculty at the
Robotics Institute, Carnegie Mellon University. He earned his PhD in Clinical
Psychology from the University of Massachusetts in Amherst and completed
Clinical Internship at the University of Maryland Medical Center. For
the past 20 years, he has conducted investigations in the theory and science
of emotion, depression, and nonverbal communication. He has co-led interdisciplinary
and inter-institutional efforts to develop advanced methods of automatic
analysis of facial expression and prosody and applied these tools to research
in human emotion, communication, biomedicine, biometrics, and human-computer
interaction. He has published over 90 papers on these topics. His research
has been supported by grants from the National Institute of Mental Health,
the National Institute of Child Health and Human Development, the National
Science Foundation, the Office of Naval Research, and the Defense Advanced
Research Projects Agency.
Automatic Facial Image Analysis
Facial expression is one of the most powerful, natural, and immediate
means for human beings to communicate their emotions and intentions. The
face can express emotion sooner than people verbalize or even realize
their feelings. To make optimal use of the information afforded by facial
expression, reliable, valid and efficient methods of measurement are critical.
Two major advances toward this goal were the human-observer-based Facial Action Coding System (FACS) and facial electromyography (EMG). The third major advance - automatic facial image analysis - combines the best features of FACS and EMG: Comprehensive description of facial expression (FACS) and quantitative, automatic measurement, which was previously possible only by using invasive facial sensors (EMG).
This talk reviews previous approaches to facial measurement (FACS and
facial EMG) and the advances in automatic facial image analysis they inform.
It reviews technical and conceptual challenges that lay ahead and the
approaches of leading investigators. It describes capabilities and limitations
of current systems, applications in emotion and social interaction, and
what we have already learned using these new systems about the configuration
and timing of facial expression.
Presentation
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Keynote lecture presented at Measuring Behavior 2005 , 5th International Conference on Methods and Techniques in Behavioral Research, 30 August - 2 September 2005, Wageningen, The Netherlands.