Dragoş Datcu
Léon Rothkrantz
ABSTRACT
The paper highlights the performance of video sequence-oriented facial expression recognition using Active Appearance Model -- AAM, in a comparison with the analysis based on still pictures. The AAM is used to extract relevant information regarding the shapes of the faces to be analyzed. Specific key points from a Facial Characteristic Point - FCP model are used to derive the set of features. These features are used for the classification of the expressions of a new face sample into the prototypic emotions. The classification method uses Support Vector Machines.
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