Abstract
Many people believe that emotions and subjective feelings are one and the same and that a goal of human-centered computing is emotion recognition. The first belief is outdated; the second mistaken. For human-centered computing to succeed, a different way of thinking is needed. Emotions are species-typical patterns that evolved because of their value in addressing fundamental life tasks. Emotions consist of multiple components, of which subjective feelings may be one. They are not directly observable, but inferred from expressive behavior, self-report, physiological indicators, and context. I focus on expressive facial behavior because of its coherence with other indicators and research. Among the topics included are measurement, timing, individual differences, dyadic interaction, and inference. I propose that design and implementation of perceptual user interfaces may be better informed by considering the complexity of emotion, its various indicators, measurement, individual differences, dyadic interaction, and problems of inference.
A previous version of this paper was originally published in the Proceedings of the ACM International Conference on Multimodal Interfaces, Banff, Canada, 2006 (Copyright © ACM Press).
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Cohn, J.F. (2007). Foundations of Human Computing: Facial Expression and Emotion. In: Huang, T.S., Nijholt, A., Pantic, M., Pentland, A. (eds) Artifical Intelligence for Human Computing. Lecture Notes in Computer Science(), vol 4451. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72348-6_1
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DOI: https://doi.org/10.1007/978-3-540-72348-6_1
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