西安电子科技大学学报（自然科学版）Issue(3)：115-121,7.DOI:10.3969/j.issn.1001-2400.2015.03.020
近邻样本协作表示的人脸识别算法
Face recognition using collaborative representation with neighbors
摘要
Abstract
An improved face recognition algorithm using the collaborative representation with nearer neighbors of the testing image is proposed.As a measurement to find the neighboring testing sample,the correlation coefficient between the testing sample and training samples is calculated in the Gabor-feature space.Neighbors of the testing sample compose the compact over-completed dictionary which is variable for different testing samples.The testing image is represented collaboratively by the variable"thickness"compact dictionary and the sparse representation coefficient is calculated with l2 minimization.The error between the reconstructed image and the testing image categorizes the testing image. This proposed algorithm has been carried out in database of FERET,ORL and AR with variations of lighting,expression, pose,and occlusion.Extensive experiments demonstrate that the proposed approach is superior both in recognition rate and in speed.关键词
Gabor/相关系数/近邻样本/协作表示/人脸识别Key words
Gabor/correlators/neighbors/collaborative representation/face recognition分类
信息技术与安全科学引用本文复制引用
魏冬梅,周卫东..近邻样本协作表示的人脸识别算法[J].西安电子科技大学学报（自然科学版）,2015,(3):115-121,7.基金项目
山东省高等学校科技计划资助项目(J14LN06) （J14LN06）
