Component-based cascade linear discriminant analysis for face recognition | |
Zhang, WC; Shan, SG; Gao, W; Chang, YZ; Cao, B | |
刊名 | ADVANCES IN BIOMETRIC PERSON AUTHENTICATION, PROCEEDINGS
![]() |
2004 | |
卷号 | 3338页码:288-295 |
ISSN号 | 0302-9743 |
英文摘要 | This paper presents a novel face recognition method based on cascade Linear Discriminant Analysis (LDA) of the component-based face representation. In the proposed method, a face image is represented as four components with overlap at the neighboring area rather than a whole face patch. Firstly, LDA is conducted on the principal components of each component individually to extract component discriminant features. Then, these features are further concatenated to undergo another LDA to extract the final face descriptor, which actually have assigned different weights to different component features. Our experiments on the FERET face database have illustrated the effectiveness of the proposed method compared with the traditional Fisherface method both for face recognition and verification. |
WOS研究方向 | Computer Science |
语种 | 英语 |
出版者 | SPRINGER-VERLAG BERLIN |
WOS记录号 | WOS:000226133000031 |
内容类型 | 期刊论文 |
源URL | [http://119.78.100.204/handle/2XEOYT63/13811] ![]() |
专题 | 中国科学院计算技术研究所期刊论文_英文 |
通讯作者 | Zhang, WC |
作者单位 | 1.Harbin Inst Technol, Sch Comp Sci & Technol, Harbin 150001, Peoples R China 2.CAS, ICT, ISVISION, Joint R&D Lab Face Recognit, Beijing 100080, Peoples R China |
推荐引用方式 GB/T 7714 | Zhang, WC,Shan, SG,Gao, W,et al. Component-based cascade linear discriminant analysis for face recognition[J]. ADVANCES IN BIOMETRIC PERSON AUTHENTICATION, PROCEEDINGS,2004,3338:288-295. |
APA | Zhang, WC,Shan, SG,Gao, W,Chang, YZ,&Cao, B.(2004).Component-based cascade linear discriminant analysis for face recognition.ADVANCES IN BIOMETRIC PERSON AUTHENTICATION, PROCEEDINGS,3338,288-295. |
MLA | Zhang, WC,et al."Component-based cascade linear discriminant analysis for face recognition".ADVANCES IN BIOMETRIC PERSON AUTHENTICATION, PROCEEDINGS 3338(2004):288-295. |
个性服务 |
查看访问统计 |
相关权益政策 |
暂无数据 |
收藏/分享 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论