Abstract
In this paper, a fully automatic, real-time system is proposed to recognize seven basic facial expressions (angry, disgust, fear, happiness, neutral, sadness and surprise), which is insensitive to illumination changes. First, face is located and normalized based on an illumination insensitive skin model and face segmentation; then, the basic Local Binary Patterns (LBP) technique, which is invariant to monotonic grey level changes, is used for facial feature extraction; finally, a coarse-to-fine scheme is used for expression classification. Theoretical analysis and experimental results show that the proposed system performs well in variable illumination and some degree of head rotation.
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Feng, X., Pietikäinen, M., Hadid, A., Xie, H. (2005). A Novel Real Time System for Facial Expression Recognition. In: Tao, J., Tan, T., Picard, R.W. (eds) Affective Computing and Intelligent Interaction. ACII 2005. Lecture Notes in Computer Science, vol 3784. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11573548_32
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DOI: https://doi.org/10.1007/11573548_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29621-8
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