[1]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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Face recognition based on the linear representation model without residual estimation

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 9 Number of periods: 2014 3 Page number: 285-291 Column: 学术论文—机器感知与模式识别 Public date: 2014-06-25
Title:
Face recognition based on the linear representation model without residual estimation
Author(s):
LIU Xunli1;  GONG Xun1;  WANG Guoyin1; 2
1. School of Information Science and Technology, Southwest Jiaotong University, Chengdu 610031, China;
2. Institute of Computer Science and Technology, Chongqing University of Posts and elecommunications, Chongqing 400065, China
Keywords:
linear representation; residual estimation; likelihood estimation; Dantzig selector model; face recognition
CLC:
TP391
DOI:
10.3969/j.issn.1673-4785.201309065
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.
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