Feature space locality constraint for kernel based nonlinear discriminant analysis
Lei, Zhen1; Mang, Zhiwei; Li, Stan Z.
2012-07-01
发表期刊PATTERN RECOGNITION
卷号45期号:7页码:2733-2742
文章类型Article
摘要Subspace learning is an important approach in pattern recognition. Nonlinear discriminant analysis (NDA), due to its capability of describing nonlinear manifold structure of samples, is considered to be more powerful to undertake classification tasks in image related problems. In kernel based NDA representation, there are three spaces involved, i.e., original data space, implicitly mapped high dimension feature space and the target low dimension subspace. Existing methods mainly focus on the information in original data space to find the most discriminant low dimension subspace. The implicit high dimension feature space plays a role that connects the original space and the target subspace to realize the nonlinear dimension reduction, but the sample geometric structure information in feature space is not involved. In this work, we try to utilize and explore this information. Specifically, the locality information of samples in feature space is modeled and integrated into the traditional kernel based NDA methods. In this way, both the sample distributions in original data space and the mapped high dimension feature space are modeled and more information is expected to be explored to improve the discriminative ability of the subspace. Two algorithms, named FSLC-KDA and FSLC-KSR. are presented. Extensive experiments on ORL, Extended-YaleB, PIE, Multi-PIE and FRGC databases validate the efficacy of the proposed method. (C) 2012 Elsevier Ltd. All rights reserved.
关键词Locality Constraint Feature Space Nonlinear Discriminant Analysis Face Recognition
WOS标题词Science & Technology ; Technology
关键词[WOS]FACE RECOGNITION ; DIMENSIONALITY REDUCTION ; ILLUMINATION ; FRAMEWORK ; POSE
收录类别SCI
语种英语
WOS研究方向Computer Science ; Engineering
WOS类目Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号WOS:000302451000023
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/7950
专题模式识别国家重点实验室_生物识别与安全技术研究
作者单位1.Chinese Acad Sci, Inst Automat, Ctr Biometr & Secur Res, Beijing 100190, Peoples R China
2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
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Lei, Zhen,Mang, Zhiwei,Li, Stan Z.. Feature space locality constraint for kernel based nonlinear discriminant analysis[J]. PATTERN RECOGNITION,2012,45(7):2733-2742.
APA Lei, Zhen,Mang, Zhiwei,&Li, Stan Z..(2012).Feature space locality constraint for kernel based nonlinear discriminant analysis.PATTERN RECOGNITION,45(7),2733-2742.
MLA Lei, Zhen,et al."Feature space locality constraint for kernel based nonlinear discriminant analysis".PATTERN RECOGNITION 45.7(2012):2733-2742.
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