电子学报2013，Vol.41Issue(5)：987-991,5.DOI:10.3969/j.issn.0372-2112.2013.05.024
基于低秩子空间恢复的联合稀疏表示人脸识别算法
Face Recognition of Joint Sparse Representation Based on Low-Rank Subspace Recovery
摘要
Abstract
In consideration of the cast shadows,specularities,occlusions and corruptions in the images that violate the lowrank structure,a novel recognition method of joint sparse representation based on low-rank subspace recovery is proposed.Firstly,using all training images of each class to form a data matrix D,we can decompose D as the sum of a low-rank matrix A and a sparse error matrix E,where A denotes the“clean”images which follow strictly the low-rank subspace structure and E accounts for cast shadows,specularities,occlusions and corruptions in the images that violate the low-rank structure.Then the test sample can be represented as the linear combination of dictionary which is composed of low rank matrix and error matrix,using the sparse approximation of this two parts calculates the residual which used for classification.Experiment results show that the algorithm is effective and effectively improve the recognition accuracy.关键词
人脸识别/稀疏表示/联合稀疏/低秩子空间恢复Key words
face recognition/ sparse representation/joint sparse/ low-rank subspace recovery分类
信息技术与安全科学引用本文复制引用
胡正平,李静..基于低秩子空间恢复的联合稀疏表示人脸识别算法[J].电子学报,2013,41(5):987-991,5.基金项目
国家自然科学基金(No.61071199) （No.61071199）
河北省自然科学基金(No.F2010001297) （No.F2010001297）
