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Context-Independent Facial Action Unit Recognition Using Shape and Gabor Phase Information Host Publication: Affective Computing and Intelligent Interaction Authors: I. Gonzalez, H. Sahli, V. Enescu and W. Verhelst Publisher: Springer Publication Year: 2011 Number of Pages: 10 ISBN: 978-3-642-24599-2
Abstract: In this paper we investigate the combination of shape features and Phase-based Gabor features for context-independent Action Unit Recognition. For our recognition goal, three regions of interest have been devised that efficiently capture the AUs activation/deactivation areas. In each of these regions a feature set consisting of geometrical and histogram of Gabor phase appearance-based features have been estimated. For each Action Unit, we applied Adaboost for feature selection, and used a binary SVM for context-independent classification. Using the Cohn-Kanade database, we achieved an average F 1 score of 93.8% and an average area under the ROC curve of 97.9 %, for the 11 AUs considered. External Link.
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