CASIA OpenIR  > 09年以前成果
Automatic 3D face recognition using discriminant common vectors
Zhong, C; Tan, T; Xu, CH; Li, JW; Zhang, D; Jain, AK
Source PublicationADVANCES IN BIOMETRICS, PROCEEDINGS
2006
Volume3832Pages:85-91
SubtypeArticle
AbstractIn this paper we propose a fully automatic scheme for 3D face recognition. In our scheme, the original 3D data is automatically converted into the normalized 3D data, then the discriminant common vector (DCV) is introduced for 3D face recognition. We also compare DCV with two common methods, i.e., principal component analysis (PCA) and linear discriminant analysis (LDA). Our experiments are based on the CASIA 3D Face Database, a challenging database with complex variations. The experimental results show that DCV is superior to the other two methods.
WOS HeadingsScience & Technology ; Technology
Indexed ByISTP ; SCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Theory & Methods
WOS IDWOS:000235768300012
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/9302
Collection09年以前成果
AffiliationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100080, Peoples R China
Recommended Citation
GB/T 7714
Zhong, C,Tan, T,Xu, CH,et al. Automatic 3D face recognition using discriminant common vectors[J]. ADVANCES IN BIOMETRICS, PROCEEDINGS,2006,3832:85-91.
APA Zhong, C,Tan, T,Xu, CH,Li, JW,Zhang, D,&Jain, AK.(2006).Automatic 3D face recognition using discriminant common vectors.ADVANCES IN BIOMETRICS, PROCEEDINGS,3832,85-91.
MLA Zhong, C,et al."Automatic 3D face recognition using discriminant common vectors".ADVANCES IN BIOMETRICS, PROCEEDINGS 3832(2006):85-91.
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