Correlation between computer recognized facial emotions and informed emotions during a casino computer game
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Date
2012
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University of New Brunswick
Abstract
Emotions play an important role for everyday communication. Different methods
allow computers to recognize emotions. Most are trained with acted emotions and it is
unknown if such a model would work for recognizing naturally appearing emotions. An
experiment was setup to estimate the recognition accuracy of the emotion recognition
software SHORE, which could detect the emotions angry, happy, sad, and surprised.
Subjects played a casino game while being recorded. The software recognition was
correlated with the recognition of ten human observers. The results showed a strong
recognition for happy, medium recognition for surprised, and a weak recognition for sad
and angry faces. In addition, questionnaires containing self-informed emotions were
compared with the computer recognition, but only weak correlations were found.
SHORE was able to recognize emotions almost as well as humans were, but if humans
had problems to recognize an emotion, then the accuracy of the software was much
lower.