| 基于线性判别分析的加权零空间算法及在人脸识别中的应用 |
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| 引用本文： | 张玉华,王欣.基于线性判别分析的加权零空间算法及在人脸识别中的应用[J].山东大学学报(工学版),2009,39(6):31-34. |
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| 作者姓名： | 张玉华 王欣 |
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| 作者单位： | 张玉华：山东大学医学院， 山东 济南 250012;
张玉华 王欣：山东大学信息科学与工程学院， 山东 济南 250100 |
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| 摘 要： | 线性判别分析(LDA)用于人脸识别时,存在因训练样本不足引起类内散布矩阵奇异的小样本问题.基于LDA的传统零空间方法首先去掉总体散布矩阵的零空间进行降维,可以避免小样本问题.提出了一种加权零空间特征提取方法,并对加权系数进行了讨论.在人脸数据库上的实验结果验证了其有效性.
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| 关 键 词： | null |
| 收稿时间： | 2009-04-01 |
A LDA-based weighted null space algorithm in face recognition |
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| ZHANG Yu-hua,WANG Xin.A LDA-based weighted null space algorithm in face recognition[J].Journal of Shandong University of Technology,2009,39(6):31-34. |
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| Authors: | ZHANG Yu-hua WANG Xin |
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| Abstract: | Linear discriminant analysis(LDA) often encounters a small-sample-size(SSS) problem when used in face recognition because there are not enough trainingsamples and the within scatter matrix is singular. The traditional LDA based null space algorithm can effectively avoid the SSS problem by first removing the null space of totalscatter matrix. A new feature extraction method called weighted null space was proposed, and the selection of weight parameters was discussed. Experimental results on face databases demonstrated its validity. |
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| Keywords: | face recognition null space linear discriminant analysis LDA |
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