Gabor-2DLDA: Face Recognition using Gabor Features and 2D Linear Discriminant Analysis

摘要：

An effective face recognition method is described in the proposed paper, which is based on Gabor Wavelets and 2D Linear Discriminant Analysis (Gabor-2DLDA).Although Gabor features has been recognized as one of the most successful face representations,its huge number of features often brings about the problem of curse of dimensionality.In this paper,we use Gabor feature matrix to represent the facial features,and then apply 2DLDA to derive subspaees from Gabor feature matrix,thus effectively addressing the issue of dimensional disaster and avoiding the singularity problem of linear discriminant analysis method. Finally,Support Vector Machine(SVM)is applied to classify the extracted face features.Experimental results on ORL database and subset of CAS-PEAL database show that the combination of Gabor 2DLDA with SVM can achieve promising results.

关键词： Gabor wavelets 2DLDA SVM face recognition

作者: Xiao-ming Wang Chang Huang Jin-gao Liu

作者单位: Dept. of Information Science and Technology East China Normal University Shanghai, China Dept. of Te Dept. of Information Science and Technology East China Normal University Shanghai, China

会议类型: 国际会议

会议名称: 2009 Second International Conference on Intelligent Computation Technology and Automation(2009 第二届IEEE智能计算与自动化国际会议 ICICTA 2009)

会议地点: 长沙

会议语种:英文

页码: 608-610

在线出版日期: 2009-10-10（万方平台首次上网日期，不代表论文的发表时间）