Context-independent facial action unit recognition using shape and gabor phase information

Authors:
Isabel Gonzalez;Hichem Sahli;Valentin Enescu;Werner Verhelst
Affiliations:
Vrije Universiteit Brussel, AVSP, Department ETRO, VUB-ETRO, Brussels, Belgium;Vrije Universiteit Brussel, AVSP, Department ETRO, VUB-ETRO, Brussels, Belgium;Vrije Universiteit Brussel, AVSP, Department ETRO, VUB-ETRO, Brussels, Belgium;Vrije Universiteit Brussel, AVSP, Department ETRO, VUB-ETRO, Brussels, Belgium and Institute for Broadband Technology - IBBT
Venue:
ACII'11 Proceedings of the 4th international conference on Affective computing and intelligent interaction - Volume Part I
Year:
2011

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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 F1 score of 93.8% and an average area under the ROC curve of 97.9 %, for the 11 AUs considered.