期刊文献+

基于局部保持投影的鉴别最大间距准则 被引量:17

Discriminant Maximum Margin Criterion Based on Locality Preserving Projections
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摘要 提出一种基于流形学习的特征提取方法——鉴别最大间距准则.该方法采用线性投影,保留最优的局部和全局信息数据集.试图找到具有最好鉴别能力的原始信息,使类间离散度最大的同时类内离散尽可能的小.该方法在识别率上比其它方法都有较大提高,通过在YALE和JAFFE人脸库上的实验验证该方法的有效性. A manifold learning algorithm is proposed called discriminant maximum margin criterion (DMMC). It adopts linear projective maps and optimally preserves the local structure and the global information of the data set simultaneously. DMMC tries to find the intrinsic manifold that discriminates different face classes best by maximizing the between-class scatter and minimizing the within-class scatter. The recognition rate of the proposed algorithm exceeds those of the single PCA, Fisherfaces, MMC and LPP greatly. Experimental results on YALE and JAFFE face databases indicate that the proposed algorithm is effective.
出处 《模式识别与人工智能》 EI CSCD 北大核心 2010年第2期178-185,共8页 Pattern Recognition and Artificial Intelligence
基金 国家自然科学基金资助项目(No.60873019)
关键词 人脸识别 特征提取 子空间 线性鉴别分析(LDA) 局部保持投影(LPP) Face Recognition, Feature Extraction, Subspace, Linear Discriminant Analysis ( LDA),Locality Preserving Projection (LPP)
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参考文献11

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二级参考文献41

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共引文献114

同被引文献179

  • 1杨健,杨静宇,叶晖.Fisher线性鉴别分析的理论研究及其应用[J].自动化学报,2003,29(4):481-493. 被引量:97
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  • 3欧阳怡彪,蒲晓蓉,章毅.基于小波和非负稀疏矩阵分解的人脸识别方法[J].计算机应用研究,2006,23(10):159-162. 被引量:7
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二级引证文献27

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