JOURNAL OF MULTIMEDIA (JMM)
ISSN : 1796-2048
Volume : 1    Issue : 5    Date : August 2006

Spontaneous Emotional Facial Expression Detection
Zhihong Zeng, Yun Fu, Glenn I. Roisman, Zhen Wen, Yuxiao Hu and  Thomas S. Huang
Page(s): 1-8
Full Text:
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Abstract
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.

Index Terms
affective computing, facial expression, one-class classification, emotion recognition