高技术通讯2017，Vol.27Issue(6)：495-505,11.DOI:10.3772/j.issn.1002-0470.2017.06.002
共享空间基-逐类剩余空间基混合稀疏表示人脸识别算法
An algorithm for sparse representation of face recognition using shared space basis-class wise residual space basis hybridization
摘要
Abstract
In view of the ordinary sample training dictionary learning ' s deficiency of unusing class common information , an algorithm for sparse representation of face recognition using shared space basis -class wise remaining space basis hybridization is proposed based on introducing shared space and remaining space associated with classes .The algo-rithm extracts the PCA ( principal component analysis ) features of training samples , and acquires the unlabeled shared space basis and its reconstruction samples to obtain class common information ; then , obtains a differential training set by combining the original samples , and constructs a class specific remaining basis by introduing inter class difference information;and finally , obtains the hybrid dictionary by combining the shared space common basis and the basis of class-wise remaining space , and then classfies the testing samples by using of residual error SRC ( sparse representation classification ) criterion.This method not only makes full use of the orthogonal property of the hybrid dictionary , but also gives full play to the discriminating ability of the remaining space and the role of sparse approximation of shared information , making the close combination of structured dictionaries with pattern classification.The results of the experiments on facial databases of AR ,CMU PIE,Extended Yale B verify the pro-posed algorithm ' s effectiveness .关键词
混合字典/共享空间/剩余空间/人脸识别/稀疏表示/逐类剩余空间Key words
hybrid dictionary/shared space/residual space/face recognition/sparse representation/class-wise remaining space引用本文复制引用
胡正平,刘立真..共享空间基-逐类剩余空间基混合稀疏表示人脸识别算法[J].高技术通讯,2017,27(6):495-505,11.基金项目
国家自然科学基金(61071199)和河北省自然科学基金(F2016203422)资助项目. （61071199）
