Toward Computational Model of Emotion from Individual Difference in Perceiving Facial Expressions
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We propose a computational model for identifying emotional state of a facial expression from appraisal scores given by human observers utilizing their differences in perception. The appraisal model of human emotion is adopted as the basis of this evaluation process with appraisal variables as output. We investigated the performance for both categorical and continuous representation of the variables appraised by human observers. Analysis of the data exhibits higher degree of agreement between estimated Indian ratings and the available reference when these are rated through continuous domain. We also observed that emotional state with negative valence are influential in the perception of hybrid emotional state like ‘Surprise’, only when appraisal variables are labeled through categories of emotions. Thus, the proposed method has implications in developing software to detect emotion using appraisal variables in continuous domain, perceived from facial expression of an agent (or human subject). Further, this model can be customized to include cultural variability in recognizing emotions.
KeywordsAppraisal variable Computational model Emotion perception Facial expressions Kernel density estimation
The authors would like to thank the subjects participated in the experiments. This research work is self funded.
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