Face Recognition Using Different Classifier Fusion Approaches

摘要：

In this paper, three well-known feature extraction methods including BDPCA, PCA and LDA have been applied to visible and infrared images and the nearest neighbor method has been used to classify faces.After classification of extracted features, Dempster-Shafer, Fuzzy Integral and Decision Template methods are used to fuse the results of infrared and visible images distinctly. Considering the fact that infrared and visible images have their complementary features, a better recognition rate can be achieved by simultaneous use of these features. The complementary approach uses the three mentioned fusion techniques to combine the results of classifiers which have been trained using extracted features of infrared and visible corresponding images utilizing BDPCA method. The experimental results show that among three fusion schemes, best result is achieved by combination of classifiers related to complementary approach using Fuzzy Integral, while other fusion schemes have also improved the final recognition rate.

关键词： Face recognition Infrared and Visible images classifier Fusion Fuzzy Integral Decision Template Dempster-Shafer

作者: N.Tajbakhsh B.Moshiri

作者单位: Control and Intelligent Processing Center of Excellence,School of Electrical and Computer Engineering Tehran University Tehran, Iran

会议类型: 国际会议

会议名称: The International Colloquium on Onformation Fusion 2007(2007年国际信息融合研讨会)

会议地点: 西安

会议语种:英文

页码: 296-301

在线出版日期: 2007-08-22（万方平台首次上网日期，不代表论文的发表时间）