CASIA OpenIR  > 09年以前成果
Gabor feature selection for face recognition using improved AdaBoost learning
Shen, LL; Bai, L; Bardsley, D; Wang, YS; Li, SZ; Sun, Z; Tan, T; Pankanti, S; Chollet, G; Zhang, D
Source PublicationADVANCES IN BIOMETRIC PERSON AUTHENTICATION, PROCEEDINGS
2005
Volume3781Pages:39-49
SubtypeArticle
AbstractThough AdaBoost has been widely used for feature selection and classifier learning, many of the selected features, or weak classifiers, are redundant. By incorporating mutual information into AdaBoost, we propose an improved boosting algorithm in this paper. The proposed method fully examines the redundancy between candidate classifiers and selected classifiers. The classifiers thus selected are both accurate and non-redundant. Experimental results show that the strong classifier learned using the proposed algorithm achieves a lower training error rate than AdaBoost. The proposed algorithm has also been applied to select discriminative Gabor features for face recognition. Even with the simple correlation distance measure and 1-NN classifier, the selected Gabor features achieve quite high recognition accuracy on the FERET database, where both expression and illumination variance exists. When only 140 features are used, the selected features achieve as high as 95.5% accuracy, which is about 2.5% higher than that of features selected by AdaBoost.
WOS HeadingsScience & Technology ; Technology
WOS KeywordINVARIANT OBJECT RECOGNITION ; ALGORITHMS ; SPACE
Indexed ByISTP ; SCI
Language英语
WOS Research AreaComputer Science ; Imaging Science & Photographic Technology
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Theory & Methods ; Imaging Science & Photographic Technology
WOS IDWOS:000233430300006
Citation statistics
Cited Times:12[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/9161
Collection09年以前成果
Affiliation1.Univ Nottingham, Sch Comp Sci & IT, Nottingham NG7 2RD, England
2.Chinese Acad Sci, Inst Automat, Beijing 100864, Peoples R China
Recommended Citation
GB/T 7714
Shen, LL,Bai, L,Bardsley, D,et al. Gabor feature selection for face recognition using improved AdaBoost learning[J]. ADVANCES IN BIOMETRIC PERSON AUTHENTICATION, PROCEEDINGS,2005,3781:39-49.
APA Shen, LL.,Bai, L.,Bardsley, D.,Wang, YS.,Li, SZ.,...&Zhang, D.(2005).Gabor feature selection for face recognition using improved AdaBoost learning.ADVANCES IN BIOMETRIC PERSON AUTHENTICATION, PROCEEDINGS,3781,39-49.
MLA Shen, LL,et al."Gabor feature selection for face recognition using improved AdaBoost learning".ADVANCES IN BIOMETRIC PERSON AUTHENTICATION, PROCEEDINGS 3781(2005):39-49.
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