Collaborative representation Bayesian face recognition  

作　　者：Jufu FENG Xiao MA Wenjing ZHUANG 

机构地区：[1]School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China

出　　处：《Science China(Information Sciences)》2017年第4期228-230,共3页中国科学（信息科学）（英文版）

基　　金：supported by National Natural Science Foundation of China (Grant No. 61333015);National Basic Research Program of China (973) (Grant No. 2011CB302400)

摘　　要：In recent years,a series of subspace methods,named the collaborative representation based methods,have aroused researchers’interests.Inspired by the idea of sparse coding,Wright et al.proposed the sparse representation based classification（SRC）method.SRC encodes a query sample as a linear combination of all subjects’training samples with sparsity constraint and then classifies it by evaluating which class has the minimal coding residual.In recent years,a series of subspace methods,named the collaborative representation based methods,have aroused researchers’interests.Inspired by the idea of sparse coding,Wright et al.proposed the sparse representation based classification（SRC）method.SRC encodes a query sample as a linear combination of all subjects’training samples with sparsity constraint and then classifies it by evaluating which class has the minimal coding residual.

关 键 词：SRC CRC 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]