Spontaneous Emotional Facial Expression Detection

Change in a speaker's emotion is a fundamental component in human communication. Automatic recognition of spontaneous emotion would significantly impact human-computer interaction and emotion-related studies in education, psychology and psychiatry. In this paper, we explore methods for detecting emotional facial expressions occurring in a realistic human conversation setting--the Adult Attachment Interview (AAI). Because non-emotional facial expressions have no distinct description and are expensive to model, we treat emotional facial expression detection as a one-class classification problem, which is to describe target objects (i.e., emotional facial expressions) and distinguish them from outliers (i.e., non-emotional ones). Our preliminary experiments on AAI data suggest that one-class classification methods can reach a good balance between cost (labeling and computing) and recognition performance by avoiding non-emotional expression labeling and modeling.

• Type: Journal
• Year: 2006
• Where: JMM2
• Authors: Zhihong Zeng, Yun Fu, Glenn I. Roisman, Zhen Wen, Yuxiao Hu, Thomas S. Huang
• Keywords: Emotional Facial Expressions, Facial Expression Detection, JMM2 2006, Non-emotional Facial Expressions