CASIA OpenIR  > 模式识别国家重点实验室  > 生物识别与安全技术研究
Contextual constraints based linear discriminant analysis
Lei, Zhen1; Li, Stan Z.
AbstractLinear feature extraction methods such as LDA have achieved great success in pattern recognition and image processing area. For most existing methods, the image data is usually transformed into a vector representation and the contextual information among pixels is not exploited. However, image data distribute sparsely in high-dimension feature space and the dependence among neighboring pixels is important to represent a natural image. Therefore, in this paper, we propose a novel image contextual constraint based linear discriminant analysis (CCLDA) method by taking into account the pixel dependence of an image in subspace learning process. In this way, a more discriminative subspace could be learned especially in. the case of small sample size. Extensive experiments on ORL, Extended Yale-B, PIE and FRGC databases validate the efficacy of the proposed method. (C) 2010 Elsevier B.V. All rights reserved.
KeywordContextual Constraint Discriminant Analysis Face Recognition
WOS HeadingsScience & Technology ; Technology
Indexed BySCI
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000287422900010
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Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Affiliation1.Chinese Acad Sci, Ctr Biometr & Secur Res, Beijing 100190, Peoples R China
2.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Lei, Zhen,Li, Stan Z.. Contextual constraints based linear discriminant analysis[J]. PATTERN RECOGNITION LETTERS,2011,32(4):626-632.
APA Lei, Zhen,&Li, Stan Z..(2011).Contextual constraints based linear discriminant analysis.PATTERN RECOGNITION LETTERS,32(4),626-632.
MLA Lei, Zhen,et al."Contextual constraints based linear discriminant analysis".PATTERN RECOGNITION LETTERS 32.4(2011):626-632.
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