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This paper describes a computational study regarding the way real humans manifest their facial expressions and emotions and how other people perceive that when applied to virtual humans. We propose a new metric for measuring individuals' emotion style where subjects were recorded while expressing the six basic emotions (happiness, fear, disgust, anger, surprise and sadness). With this metric, we were able to group the subjects into four different clusters and provide evidence that shows a visual correlation between the groups and the video footage. After applying the styles in virtual humans, a survey was also applied to lay people in order to understand how emotion style is perceived and identified by the general public. The survey not only indicated that people are in fact able to perceive an individual's emotion style regardless of facial geometry, but also showed that there seems to be a particular style that is considered more sympathetic and approachable when compared to others.

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