Real-Time facial expression recognition system based on HMM and feature point localization

Authors:
Yumei Fan;Ning Cheng;Zhiliang Wang;Jiwei Liu;Changsheng Zhu
Affiliations:
University of Science and Technology, Beijing;University of Science and Technology, Beijing;University of Science and Technology, Beijing;University of Science and Technology, Beijing;University of Science and Technology, Beijing
Venue:
ACII'05 Proceedings of the First international conference on Affective Computing and Intelligent Interaction
Year:
2005

Citing 2
Cited 0

Skin-Color Extraction in Images with Complex Background and Varying Illumination

WACV '02 Proceedings of the Sixth IEEE Workshop on Applications of Computer Vision
Facial action recognition for facial expression analysis from static face images

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Quantified Score

Hi-index	0.00

Visualization

Abstract

It is difficult for computer to recognize facial expression in real-time. Until now, no good method is put forward to solve this problem in and abroad. In this paper, we present an effective automated system that we developed to recognize facial gestures in real-time. According to psychologists’ facial expression classification, we define four basic facial expressions and localize key facial feature points exactly then extract facial components’ contours. We analyze and record facial components’ movements using information in sequential frames to recognize facial gestures. Since different facial expressions can have some same movements, it is necessary to use a good facial expression model to describe the relation between expression states and observed states of facial components’ movements for achieving a good recognition results. HMM is such a good method which can meet our requirement. We present a facial expression model based on HMM and get good real-time recognition results.