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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Context-Independent Facial Action Unit Recognition Using Shape and Gabor Phase Information
verfasst von : Isabel Gonzalez, Hichem Sahli, Valentin Enescu, Werner Verhelst
Erschienen in: Affective Computing and Intelligent Interaction
Verlag: Springer Berlin Heidelberg
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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.