Abstract
Facial emotion and expression recognition is the study of facial expressions to infer the emotional state of a person. A camera captures video or images of a person’s face and algorithms automatically, without the help of a human operator, detect his/her expressions to infer his/her underlying emotional state. There has been an increased interest in this field in the past decade, and a system that accomplishes these tasks in unconstrained settings is a realizable goal. In this chapter, we will discuss the process by which a human expresses an emotion; how it is perceived by the human visual system at a low level; how prediction of emotion is made by a human; and publicly available datasets currently used by researchers in the field.
Portions of this chapter are © IEEE 2013, 2014 and appeared in “Background suppressing Gabor energy filtering,” “Score-based facial emotion recognition,” and “Vision and attention theory-based sampling for continuous facial emotion recognition”.
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Acknowledgment
This work was supported in part by the National Science Foundation Integrative Graduate Education and Research Traineeship (IGERT) in Video Bioinformatics (DGE-0903667). Alberto Cruz is an IGERT Fellow.
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Cruz, A.C., Bhanu, B., Thakoor, N.S. (2015). Understanding of the Biological Process of Nonverbal Communication: Facial Emotion and Expression Recognition. In: Bhanu, B., Talbot, P. (eds) Video Bioinformatics. Computational Biology, vol 22. Springer, Cham. https://doi.org/10.1007/978-3-319-23724-4_18
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