Abstract
We present a new approach for recognizing facial expressions based on two dimensions without detectable cues such as a neutral expression, which has essentially zero motion energy. To remove much of the variability due to lighting, a zero-phase whitening filter was applied. Principal component analysis(PCA) representation excluded the first one principal component as the features for facial expression recognition regardless of neutral expressions was developed. The result of facial expression recognition using a neural network model is compared with two-dimension values of internal states derived from ratings of facial expression pictures related to emotion by experimental subjects. The proposed algorithm demonstrated the ability to overcome the limitation of expression recognition based on a small number of discrete categories of emotional expressions, lighting sensitivity, and dependence on cues such as a neutral expression.
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Shin, YS., Ahn, Y.J. (2005). Facial Expression Recognition Based on Two Dimensions Without Neutral Expressions. In: Kishino, F., Kitamura, Y., Kato, H., Nagata, N. (eds) Entertainment Computing - ICEC 2005. ICEC 2005. Lecture Notes in Computer Science, vol 3711. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11558651_21
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DOI: https://doi.org/10.1007/11558651_21
Publisher Name: Springer, Berlin, Heidelberg
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