Robust Face Recognition Based on Non-negative Sparse Discriminative Low-rank Representation
作者单位：College of Information EngineeringYangzhou University
会议名称：《第30届中国控制与决策会议》
会议日期：2018年
学科分类：08[工学] 080203[工学-机械设计及理论] 0802[工学-机械工程]
关 键 词：Low-rank representation Sparse representation Structural inconsistency
摘 要：Due to occlusion or camouflage existing in the current face images,previous face recognition algorithms such as sparse representation classification algorithm do not take face damage into consideration during the training period,and therefore their testing performance will be *** this paper,we propose a novel non-negative sparse discriminative low-rank representation algorithm（NSDLRR）.First,we seek a sparse,low-rank and non-negative matrix in training ***,we add a structural inconsistency constraint on this basis,make different kinds of samples as independent as possible,thereby increasing the extra recognition ***,the test samples are classified by sparse linear *** results on different face database show that the algorithm has better performance.