PT Unknown
AU Agata Lapedriza
   David Masip
   David Sanchez
TI Emotions Classification using Facial Action Units Recognition
BT 17th International Conference of the Catalan Association for Artificial Intelligence
PY 2014
BP 55
EP 64
VL 269
DI 10.3233/978-1-61499-452-7-55
AB In this work we build a system for automatic emotion classification from image sequences. We analyze subtle changes in facial expressions by detecting a subset of 12 representative facial action units (AUs). Then, we classify emotions based on the output of these AUs classifiers, i.e. the presence/absence of AUs. We base the AUs classification upon a set of spatio-temporal geometric and appearance features for facial representation, fusing them within the emotion classifier. A decision tree is trained for emotion classifying, making the resulting model easy to interpret by capturing the combination of AUs activation that lead to a particular emotion. For Cohn-Kanade database, the proposed system classifies 7 emotions with a mean accuracy of near 90%, attaining a similar recognition accuracy in comparison with non-interpretable models that are not based in AUs detection.
ER