Using a human face in an interface
CHI '94 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The media equation: how people treat computers, television, and new media like real people and places
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
Affective computing
Face to interface: facial affect in (hu)man and machine
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Communicating facial affect: it's not the realism, it's the motion
CHI '00 Extended Abstracts on Human Factors in Computing Systems
Categorical perception of facial affect: an illusion
CHI '01 Extended Abstracts on Human Factors in Computing Systems
EMPATH: A Neural Network that Categorizes Facial Expressions
Journal of Cognitive Neuroscience
The role of the face in communication: Implications for videophone design
Interacting with Computers
Designing a large-scale video chat application
Proceedings of the 13th annual ACM international conference on Multimedia
CHI '06 Extended Abstracts on Human Factors in Computing Systems
International Journal of Human-Computer Studies
An experimental setting to measure contextual perception of embodied conversational agents
Proceedings of the international conference on Advances in computer entertainment technology
International Journal of Human-Computer Studies
HCI and the face: towards an art of the soluble
HCI'07 Proceedings of the 12th international conference on Human-computer interaction: interaction design and usability
Social navigation with the collective mobile mood monitoring system
Proceedings of the 15th International Academic MindTrek Conference: Envisioning Future Media Environments
Affect prediction from physiological measures via visual stimuli
International Journal of Human-Computer Studies
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Facial affect (or emotion) recognition is a central issue for many VMC and naturalistic computing applications. Most computational models assume "categorical perception" of facial affect, in which a benign illusion promotes robust recognition of emotional expressions even under severe degradation conditions, including temporal compression. However, this applied interest in human facial affect perception is coming at a time when the evidence for categorical perception is being challenged in the basic research literature, largely on methodological grounds. The research presented here systematically addresses the classic evidence for categorical perception of facial affect, using high-quality digital imaging and display technologies and improved research methods. In doing so, it illustrates a fruitful convergence of basic and applied research. The evidence does NOT support categorical perception of facial affect, which in turn underlines the importance of preserving high-fidelity motion information in portraying emotion. This research provides new human behavioral data on facial affect perception, and underscores the importance of careful consideration of facial affect compression methods.