Facial Expression Recognition Using Moment Invariants and Singular Value Decomposition

摘要：

This paper proposes a method of facial expressions recognition which combined moment invariants features with singular value. Moment invariants and singular value features are extracted respectively from the eyes, eyebrows and mouth regions in the facial expression images. Then these features are optimized to obtain a feature vector by Fisher linear discriminate analysis and a SVM classifier is trained as recognition. The experiments results show that the method can improve the recognition rate and has robust performance.

关键词： Moment invariants SVD SVM Facial expression Recognition

作者: Wang Guojiang Yang Guoliang Fu Kechang

作者单位: School of Control Engineering Chengdu University of Information Technology Chengdu 610225 China. School of Mechanical and Electrical Engineering Jiangxi University of Science and Technology Ganzhou

会议类型: 国际会议

会议名称: The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)

会议地点: 沈阳

会议语种:英文

页码: 132-135

在线出版日期: 2010-03-27（万方平台首次上网日期，不代表论文的发表时间）