Quantifying dynamic facial expressions under naturalistic conditions
Jayson Jeganathan1,2, Megan Campbell1,2, Matthew Hyett3
1School of Psychology, College of Engineering, Science and the Environment, University of Newcastle, Newcastle, Australia.
Abstract:
Facial affect is expressed dynamically - a giggle, grimace, or an agitated frown. However, the characterisation of human affect has relied almost exclusively on static images. This approach cannot capture the nuances of human communication or support the naturalistic assessment of affective disorders. Using the latest in machine vision and systems modelling, we studied dynamic facial expressions of people viewing emotionally salient film clips. We found that the apparent complexity of dynamic facial expressions can be captured by a small number of simple spatiotemporal states - composites of distinct facial actions, each expressed with a unique spectral fingerprint. Sequential expression of these states is common across individuals viewing the same film stimuli but varies in those with the melancholic subtype of major depressive disorder. This approach provides a platform for translational research, capturing dynamic facial expressions under naturalistic conditions and enabling new quantitative tools for the study of affective disorders and related mental illnesses.
Related Concept Videos
Facial Feedback Hypothesis
Muscles for Facial Expressions
Emotional Expression
Universal Facial Expressions
Psychologist Paul Ekman identified seven basic...
Therapeutic Communication
Verbal communication depends on language or a prescribed way of using words so that people can share information effectively. The critical aspects of verbal...


