• Korean Journal of Cognitive Science
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• v.18 no.1
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• pp.57-68
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• 2007

This study explores children's categories of emotion understanding from facial expressions onto two dimensional structure of emotion. Children of 89 from 3 to 5 years old were required to those facial expressions related the fourteen emotion terms. Facial expressions applied for experiment are used the photographs rated the degree of expression in each of the two dimensions (pleasure-displeasure dimension and arousal-sleep dimension) on a nine-point scale from 54 university students. The experimental results showed that children indicated the greater stability in arousal dimension than stability in pleasure-displeasure dimension. Emotions about sadness, sleepiness, anger and surprise onto two dimensions was understand very well, but emotions about fear, boredom were showed instability in pleasure-displeasure dimension. Specifically, 3 years old children indicated highly the perception in a degree of arousal-sleep than perception of pleasure-displeasure.

• Korean Journal of Cognitive Science
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• v.21 no.1
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• pp.127-143
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• 2010

This study explores children's sex differences of emotion discrimination from facial expressions based on two dimensional model of emotion. The study group consisted of 92 children, of 40, 52, and 64 months of age, and the rate of male and female children was male children (50%) and female children (50%). Children of 92 were required to choose facial expressions related the twelve emotion terms. Facial expressions applied for experiment are used the photographs rated the degree of expression in each of the two dimensions (pleasure-displeasure dimension and arousal-sleep dimension) on a nine-point scale from 54 university students. The experimental findings appeared that the sex differences were distinctly the arousal-sleep dimension than the pleasure-displeasure dimension. In the arousal-sleep dimensionoussleepness, anger, comfort, and loneliness' emotions showed large sex differences over 1 value. Especially, while male children showed high arousal more than female children in the emotions like 'sleepiness, anger and loneliness', female children showed high arousal more than male children in 'comfort' emotion.

• Korean Journal of Cognitive Science
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• v.12 no.1_2
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• pp.77-89
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• 2001

Applying perceptual hierarchy of facial feature points, a neural network model for recognizing facial expressions was designed. Input data were convolution values of 150 facial expression pictures by Gabor-filters of 5 different sizes and 8 different orientations for each of 39 mesh points defined by MPEG-4 SNHC (Synthetic/Natural Hybrid Coding). A set of multiple regression analyses was performed with the rating value of the affective states for each facial expression and the Gabor-filtered values of 39 feature points. The results show that the pleasure-displeasure dimension of affective states is mainly related to the feature points around the mouth and the eyebrows, while a arousal-sleep dimension is closely related to the feature points around eyes. For the filter sizes. the affective states were found to be mostly related to the low spatial frequency. and for the filter orientations. the oblique orientations. An optimized neural network model was designed on the basis of these results by reducing original 1560(39x5x8) input elements to 400(25x2x8) The optimized model could predict human affective rating values. up to the correlation value of 0.886 for the pleasure-displeasure, and 0.631 for the arousal-sleep. Mapping the results of the optimized model to the six basic emotional categories (happy, sad, fear, angry, surprised, disgusted) fit 74% of human responses. Results of this study imply that, using human principles of recognizing facial expressions, a system for recognizing facial expressions can be optimized even with a a relatively little amount of information.