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). First, faces are located and normalized based on an illumination insensitive skin model and face segmentation; then, the Local Binary Patterns (LBP) techniques, which are invariant to monotonic grey level changes, are used for facial feature extraction; finally, the Linear Programming (LP) technique is employed to classify seven facial expressions. Theoretical analysis and experimental results show that the proposed system performs well in some degree of illumination changes and head rotations. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Feng, X., Cui, L., Pietikäinen, M., & Hadid, A. (2005). Real time facial expression recognition using local binary patterns and linear programming. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3789 LNAI, pp. 328–336). Springer Verlag. https://doi.org/10.1007/11579427_33
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