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Cross-dataset learning and person-specific normalisation for automatic Action Unit detection
2015
2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG)
Automatic detection of Facial Action Units (AUs) is crucial for facial analysis systems. Due to the large individual differences, performance of AU classifiers depends largely on training data and the ability to estimate facial expressions of a neutral face. In this paper, we present a real-time Facial Action Unit intensity estimation and occurrence detection system based on appearance (Histograms of Oriented Gradients) and geometry features (shape parameters and landmark locations). Our
doi:10.1109/fg.2015.7284869
dblp:conf/fg/BaltrusaitisM015
fatcat:irmndojdpfhdrkaa2bmeck2nji