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Emotion Recognition in Facial Image Sequences Using a Combination of AAM with FACS and DBN

2010; Springer Science+Business Media; Linguagem: Inglês

10.1007/978-3-642-16584-9_67

1611-3349

Kwang-Eun Ko, Kwee-Bo Sim,

Emotion and Mood Recognition

If we want to recognize the human’s emotion via the face-to-face interaction, first of all, we need to extract the emotional features from the facial image and recognize the emotional states. . Our facial emotional feature detection and extracting based on Active Appearance Models (AAM) with Ekman’s Facial Action Coding System (FACS). Our approach to facial emotion recognition lies in the dynamic and probabilistic framework based on Dynamic Bayesian Network (DBN). The active appearance model (AAM) is a well-known method that can represent a non-rigid object, such as face, facial expression. In this paper, our approach to facial feature extraction lies in the proposed feature extraction method based on combining AAM with Facial Action Units of Facial Action Coding System (FACS) for automatically modeling and extracting the facial emotional features. Also, we use the Dynamic Bayesian Networks (DBNs) for modeling and understanding the temporal phases of facial expressions in image sequences.