[1]刘训利,龚勋,王国胤.一种基于非残差估计线性表示模型的人脸识别[J].智能系统学报,2014,9(3):285-291.[doi:10.3969/j.issn.1673-4785.201309065]
LIU Xunli,GONG Xun,WANG Guoyin.Face recognition based on the linear representation model without residual estimation[J].CAAI Transactions on Intelligent Systems,2014,9(3):285-291.[doi:10.3969/j.issn.1673-4785.201309065]
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LIU Xunli,GONG Xun,WANG Guoyin.Face recognition based on the linear representation model without residual estimation[J].CAAI Transactions on Intelligent Systems,2014,9(3):285-291.[doi:10.3969/j.issn.1673-4785.201309065]
一种基于非残差估计线性表示模型的人脸识别
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
9
期数:
2014年第3期
页码:
285-291
栏目:
学术论文—机器感知与模式识别
出版日期:
2014-06-25
- Title:
- Face recognition based on the linear representation model without residual estimation
- 关键词:
- 线性表示; 残差; 似然估计; Dantzig selector模型; 人脸识别
- Keywords:
- linear representation; residual estimation; likelihood estimation; Dantzig selector model; face recognition
- 分类号:
- TP391
- 摘要:
- Dantzig selector利用样本与残差之间的相关向量的L∞范数来约束线性表示模型, 为了克服传统的线性表示在处理表示残差时依赖于一个对残差特定的似然估计这一缺陷将这样一种处理残差的思路用于人脸识别, 提出了一种基于Dantzig selector模型的人脸识别算法, 并对Dantzig selector的一种有效的求解方法进行研究。在常用人脸库上实验表明, 基于Dantzig selector人脸识别算法在不需要对残差进行估计的情况下也能取得了很好的识别效果。
- Abstract:
- The Dantzig selector constrains the representation model with L∞ norm of the related vector between the samples and residuals, so as a result it is more convenient and more adaptive. Traditional linear representation dealing with residuals depends on specific residual likelihood estimation of residual. In order to overcome this defect, A new face recognition algorithm based on the Dantzig selector is proposed, applying the concept of dealing with the residual and a high-efficiency solution to the Dantzig selector is also studied. Experiments conducted with commonly used face databases show that the Dantzig selector achieves good results with face recognition without residual estimation.
- 参考文献/References:
-
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[6] 王大荣, 张忠占.线性回归模型中变量选择方法综述[J]. 数理统计与管理. 2010, 29(4):615-627.WANG Darong, ZHANG Zhongzhan. Variable selection for linear regression models:a survey[J]. Journal of Applied Statistics and Management. 2010, 29(4):615-627.
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[8] ZHANG L, YANG M, FENG X C. Sparse representation or collaborative representation:which helps face recognition[C]//IEEE International Conference on Computer Vision. Barcelona, Spain, 2011:471-478.
[9] TIBSHIRANI R. Regression shrinkage and selection via the lasso[J]. Journal of the Royal Statistical Society, 1996:58(1):267-288.
[10] YANG A Y, SASTRY S S, GANESH A, et al. Fast l1-minimization algorithms and an application in robust face recognition:a review[C]//IEEE International Conference on Image Processing, Hong Kong, China, 2010:1849-1852.
[11] MALIOUTOV D M, CETIN M, WILLSKY A S. Homotopy continuation for sparse signal representation[C]//IEEE International Conference on Acoustics, Speech, and Signal Processing. NewYork, USA, 2005:733-736.
[12] CANDES E, TERENCE TAO. Decoding by linear programming[J]. IEEE Transactions on Information Theory, 2005, 51(12):4203-4215.
[13] ASIF M S. Primal dual pursuit:A homotopy based algorithm for the Dantzig selector[D]. Atlanta:Georgia Institute of Technology, 2008.
[14] GEORGHIADES A S, BELHUMEUR P N, KRIEGMAN D J. From few to many:illumination cone models for face recognition under variable lighting and pose[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2001, 23(6):643-660.
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备注/Memo
收稿日期:2013-09-22。
基金项目:国家自然科学基金资助项目(61202191);中高校基本科研业务费专项资金资助项目(SWJTU12CX095)
作者简介:王国胤,男,1970年生,教授,博士生导师,博士,国际粗糙集学会常务理事兼指导委员会主席,IEEE高级会员,中国人工智能学会常务理事兼粗糙集与软计算专业委员会主任委员,中国计算机学会理事,主要研究方向为智能信息处理与人工智能,粗糙集理论等。主持国家自然科学基金、国家"863"计划等40多项国家级、省部级科研项目。组织召开了11届中国Rough集与软计算学术研讨会系列会议,并担任会议主席或共同主席。获重庆市自然科学一等奖、二等奖各1次。发表学术论文200余篇,出版著作7部,主编国际会议论文集13部;龚勋,男,1980年生,副教授,博士,中国计算机学会会员,中国人工智能学会粗糙集与软计算专业委员会委员,主要研究方向为智能图像处理及模式识别。近年来获重庆市自然科学一等奖1项;主持国家自然科学基金项目1项、中央高校基本科研业务费科技创新项目1项,参与国家自然科学基金1项、"十一五"国家科技支撑计划子项目1项。获国家发明专利1项,发表学术论文30余篇,出版专著 1部。
通讯作者:刘训利,男,1988年生,硕士研究生,主要研究方向为人脸识别、计算机视觉,542140771@qq.com。
更新日期/Last Update:
1900-01-01