Support Vector Clustering of Facial Expression Features

摘要：

Facial expression recognition is an active research area that finds a potential application in human emotion analysis. This work presents an efficient approach of facial expression features clustering based on Support Vector Clustering (SVC). Common approaches to facial expression features clustering are designed considering two main parts: (1) features extraction, and (2) features clustering. In the process of facial expression extraction, we use Gabor features can reduce data dimensional, then we tune the parameters that define the Gaussian kernel width generator for clustering. Experiments on facial expression database have shown that these methods are effective to achieve facial expression features clustering.

作者: Shu-ren ZHOU Xi-ming LIANG Can ZHU

作者单位: School of Information Science and Engineering, Central South University, Changsha 410083,China Compu School of Information Science and Engineering, Central South University, Changsha 410083,China

会议类型: 国际会议

会议名称: International Conference on Intelligent Computation Technology and Automation(2008 智能计算技术与自动化国际会议 ICICTA 2008)

会议地点: 长沙

会议语种:英文

页码: 811-815

在线出版日期: 2008-10-20（万方平台首次上网日期，不代表论文的发表时间）