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Facial emotion recognition

The interest on emotional computing has been increasing as many applications were in demand by multiple markets. This paper mainly focuses on different learning methods, and has implemented several methods: Support Vector Machine (SVM) and Deep Boltzmann Machine (DBM) for facial emotion recognition. The training and testing data sets of facial emotion prediction are from FERA 2015, and geometric features and appearance features are combined together. Different prediction systems are developed and the prediction results are compared. This paper aims to design an suitable system for facial emotion recognition.