This paper addresses the problem of facial expressions recognition using principal component analysis and independent component analysis onto dimension of the emotion. To reflect well the changes in facial expressions, a representation based on principal component analysis (PCA) excluded the first 2 principal components is presented, ICA representation from this PCA representation is developed. Facial expression performance in two dimensional structure was significant 90.9% in pleasure/displeasure dimension and 66.6% in the arousal/sleep dimension. The findings indicate that the two dimensional structure of emotion may reflect various emotion states as a stabled structure for the facial expression recognition.


Principal Component Analysis Facial Expression Independent Component Analysis Independent Component Analysis Emotion Word 
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© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Young-suk Shin
    • 1
  1. 1.Department of Information and telecommunication EngineeringChosun UniversityGwangjuKorea

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