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Journal Article

Using Automated Facial Expression Analysis for Emotion and Behavior Prediction

In this chapter, we propose a model of approaching facial expression detection and analysis that goes beyond category-based measurements by incorporating automated technologies that make create and automatically improve prediction models based on raw facial feature movements. Using a computer equipped with a small camera, tracking software, and machine learning (an automated form of computer generated self-enhancement), we are able to select the most relevant facial features out of the massive collection of raw data and improve the prediction model in a time- and cost-efficient way. This allows us to utilize the raw data without fitting them into predefined categories, giving us greater analytical power than conventional category-based predictions. Moreover, our suggested methodology is notably unobtrusive when compared to other behavioral measures such as physiological measures, which usually require numerous sensors to be attached to the body.

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S.J. Ahn
J.N. Bailenson
J. Fox
M.E. Jabon
Journal Name
Handbook of Emotions and Mass Media
Publication Date