[1]王科俊,邹国锋,张洁.SPCA参数对单样本人脸识别效果影响分析[J].智能系统学报,2011,6(06):531-538.
 WANG Kejun,ZOU Guofeng,ZHANG Jie.Analysis of the influence of SPCA parameters on the recognition of a single sample face[J].CAAI Transactions on Intelligent Systems,2011,6(06):531-538.
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SPCA参数对单样本人脸识别效果影响分析(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第6卷
期数:
2011年06期
页码:
531-538
栏目:
出版日期:
2011-12-25

文章信息/Info

Title:
Analysis of the influence of SPCA parameters on the recognition of a single sample face
文章编号:
1673-4785(2011)06-0531-08
作者:
王科俊邹国锋张洁
哈尔滨工程大学 自动化学院,黑龙江 哈尔滨 150001
Author(s):
WANG Kejun ZOU Guofeng ZHANG Jie
College of Automation, Harbin Engineering University, Harbin 150001, China
关键词:
人脸识别奇异值分解结合投影主分量分析奇异值扰动主分量分析衍生图像结合图像
Keywords:
face recognitionsingular value decomposition (PC)2A SPCA derived image combined image
分类号:
TP391.4
文献标志码:
A
摘要:
奇异值扰动的主分量分析(SPCA)是一种有效的单样本人脸识别方法,但SPCA算法的识别效果受参数选择的影响比较大,针对SPCA算法中衍生图像生成参数n和结合参数α的不同取值对识别效果的影响进行了分析,利用ORL人脸库和CASPEAL人脸库做了大量的实验和比较分析,实验结果表明给出的SPCA参数选取方法和取值范围是合理的,并有效地提高了SPCA算法的实际应用效果和单样本人脸识别的性能.
Abstract:
Singular value decomposition perturbation principal component analysis (SPCA) is an effective singlesample face recognition method; however, the identification results of the SPCA algorithm are seriously affected by parameter selection. In this paper, the effect on the identification, which was caused by the derived image parameter and the combined image generation parameter in the SPCA algorithm, was analyzed. Many experiments and comparative analyses were performed on the basis of the ORL face database and the CASPEAL face database. The experimental results show that the SPCA parameter selection method and the parameter range given in this paper are reasonable. In addition, reasonable parameters are effective in improving practical application of SPCA algorithms and the recognition performance of a singlesample face.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2010-09-14.
基金项目:国家“863”计划资助项目(2008AA01Z148); 黑龙江省杰出青年科学基金资助项目(JC200703);哈尔滨市科技创新人才研究专项基金资助项目(2007RFXXG009). 
通信作者:邹国锋.E-mail:zgf841122@163.com.
作者简介:
王科俊,男,1962年生,教授,博士生导师,博士,哈尔滨工程大学自动化学院副院长,哈尔滨工程大学模式识别与智能系统学科带头人.现任中国人工智能学会理事、中国人工智能学会科普工作委员会副主任、黑龙江省人工智能学会理事长、黑龙江省神经科学学会副理事长、黑龙江省神经科学学会人工智能与医学工程专业委员会主任、黑龙江省自动化学会理事.曾获得部级科技进步二等奖2项,三等奖3项,省高校科学技术一等奖1项、二等奖1项,中国船舶工业总公司优秀青年科技工作者称号,2002年黑龙江省十大杰出青年提名奖,哈尔滨工程大学首届十大杰出青年称号.主要研究方向为生物特征识别与智能监控、神经网络、计算〖LL〗生物信息学等.完成科研项目20余项,在研项目10余项.发表学术论文150余篇,出版学术专著3部,国防教材1部,主审教材2部.
邹国锋,男,1984年生,博士研究生,主要研究方向为生物特征识别与智能监控.
张洁,女,1987年生,硕士研究生,主要研究方向为生物特征识别与智能监控.
更新日期/Last Update: 2012-02-29