[1]崔鹏,张汝波.半监督系数选择法的人脸识别[J].哈尔滨工程大学学报,2012,(07):855-861.[doi:10.3969/j.issn.1006-7043.201105090]
 CUI Peng,ZHANG Rubo.A semi-supervised coefficient selection method for face recognition[J].hebgcdxxb,2012,(07):855-861.[doi:10.3969/j.issn.1006-7043.201105090]
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半监督系数选择法的人脸识别(/HTML)
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《哈尔滨工程大学学报》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2012年07期
页码:
855-861
栏目:
出版日期:
2012-07-25

文章信息/Info

Title:
A semi-supervised coefficient selection method for face recognition
文章编号:
1006-7043(2012)07-0855-07
作者:
崔鹏 张汝波
1. 哈尔滨工程大学 计算机科学与技术学院,黑龙江 哈尔滨150001; 2.哈尔滨理工大学 计算机科学与技术学院,黑龙江 哈尔滨 150080
Author(s):
CUI PengZHANG Rubo
1. College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China; 2. School of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, China
关键词:
半监督约束聚类人脸识别离散余弦变换主成分分析线性判别分析
分类号:
TP391.41
DOI:
10.3969/j.issn.1006-7043.201105090
文献标志码:
A
摘要:
针对人脸识别过程中图像数据维数过高以及需要大量类别标记的问题,提出一种半监督离散余弦变换系数选择法,用以实现数据降维并提高识别率.该算法首先将图像数据进行离散余弦变换,根据频率特征通过预掩模选取有用信息;然后进行半监督约束聚类,利用少量有标记样本的约束集,对训练图像进行聚类;根据类别搜索较高的判别系数值,获得系数选择掩模以及训练图像的投影阵.将测试图像离散余弦变换阵在此掩模上投影,计算其与训练图像投影阵距离,利用分类器进行分类.在ORL与Yale人脸数据库上的实验结果表明:所提方法的性能优于传统方法,并与主成分分析与线性判别分析进行组合,获得了90%以上的识别率.针对人脸识别过程中图像数据维数过高以及需要大量类别标记的问题,提出一种半监督离散余弦变换系数选择法,用以实现数据降维并提高识别率.该算法首先将图像数据进行离散余弦变换,根据频率特征通过预掩模选取有用信息;然后进行半监督约束聚类,利用少量有标记样本的约束集,对训练图像进行聚类;根据类别搜索较高的判别系数值,获得系数选择掩模以及训练图像的投影阵.将测试图像离散余弦变换阵在此掩模上投影,计算其与训练图像投影阵距离,利用分类器进行分类.在ORL与Yale人脸数据库上的实验结果表明:所提方法的性能优于传统方法,并与主成分分析与线性判别分析进行组合,获得了90%以上的识别率.

参考文献/References:

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备注/Memo

备注/Memo:
国家863计划资助项目(2009AA04Z215); 黑龙江省教育厅资助项目(11551086).
更新日期/Last Update: 2012-07-12