文献类型：会议论文

英文题名：Face Recognition Based on LFDA and LS-SVM

作者：Shen, Qi[1];Liu, Ruixiang[2]

第一作者：Shen, Qi

通讯作者：Shen, Q[1]

机构：[1]Beijing Univ Technol, Sch Software Engn, Beijing, Peoples R China;[2]Beijing Union Univ, Informat Coll, Beijing, Peoples R China

第一机构：Beijing Univ Technol, Sch Software Engn, Beijing, Peoples R China

通讯机构：[1]corresponding author), Beijing Univ Technol, Sch Software Engn, Beijing, Peoples R China.

会议论文集：2nd International Conference on Education Technology and Training

会议日期：DEC 13-14, 2009

会议地点：Sanya, PEOPLES R CHINA

语种：英文

外文关键词：face recognition; feature extraction; local fisher discriminant analysis (LFDA); least square version of SVM (LS-SVM)

摘要：Face recognition is one of the most challenging research topics in the field of pattern recognition and computer vision. To efficiently deal with this problem, a novel face recognition algorithm is proposed by the combination of local fisher discriminant analysis (LFDA) and least square version of SVM(LS-SVM). Experimental results on real face databases have demonstrated the better performance of the proposed algorithm.