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正则化保局鉴别分析方法

, PP. 581-587

Keywords: 保局鉴别分析,正则化,特征提取,人脸识别

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Abstract:

提出一种正则化保局鉴别分析方法(RLPDA)并将其应用于人脸识别。受样本有限制约和大量噪声干扰,保局类内散布矩阵的零特征值及小特征值估计不准确,进而影响鉴别保局投影算法的性能。结合倒数谱模型对保局类内散布矩阵的特征值进行正则化,并利用正则化后的特征值对相应的特征空间加权,使人脸空间被保留,噪声空间被削弱,而零空间则被加强。通过分析鉴别信息在数据空间的分布可发现,RLPDA方法有效利用整个特征空间的鉴别信息,有利于提高算法的识别精度,同时从原理上回避小样本问题。在FERET和UMIST人脸数据库上的识别结果表明,RLPDA是一种有效的人脸特征提取方法。

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