Low-rank representation based robust face recognition by two-dimensional whitening reconstruction

作     者：Shuo FENG Changpeng WANG Hong SHU Tingyu ZHANG Shuo FENG;Changpeng WANG;Hong SHU;Tingyu ZHANG

作者机构：School of Construction MachineryChang’an UniversityXi’an710064China School of ScienceChang’an UniversityXi’an710064China 

出 版 物：《Frontiers of Computer Science》 (中国计算机科学前沿（英文版）)

年 卷 期：2020年第14卷第4期

页      面：211-213页

核心收录：

学科分类：08[工学] 080203[工学-机械设计及理论] 0802[工学-机械工程] 

基　　金：This work was supported by the Basic Science Research of Shaanxi Province(2018JQ1038,2018JQ5059) the Special Fund for Basic Scientific Research of Central Colleagues,Chang’an University(310812171006) 

主　　题：computer representation rank 

摘      要：1 Introduction and main contributions Recently,low-rank representation(LRR)has been introduced and applied to capture the underlying low-dimensional struc-ture of data in pattern recognition and computer *** could detect the corruptions automatically during data recov-ery under mild conditions[1].In the sense of simultaneously optimizing the data representation,LRR is claimed to well capture the global structure of the data[2].