Face Recognition with Supervised Spectral Regression And Multiple Kernel SVM

摘要：

Face recognition plays an every important role in security surveillance, secure access and identity authentication. In this paper, we propose a novel face recognition method based on supervised learning. Our method consists in first extracting face feature using a supervised spectral regression, then we use multiple kernel SVM to classify face. Experimental results on Yale B face database and AR face database show the effectiveness of the proposed method.

关键词： face recognition supervised learning spectral regression multiple kernel learnin SVM

作者: Yongliang Xiao Limin Xia Wei Zhang

作者单位: School of Information Science and Engineering Central South University Changsha Hunan Province China School of Information Science and Engineering Central South University Changsha Hunan Province China

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: 343-346

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）