Nearest orthogonal matrix representation for face recognition

Zhang, Jian, Yang, Jian, Qian, Jianjun and Xu, Jiawei (2015) Nearest orthogonal matrix representation for face recognition. Neurocomputing, 151 (P1). pp. 471-480. ISSN 0925-2312

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Item Type:Article
Item Status:Live Archive

Abstract

This paper presents a simple but effective method for face recognition, named nearest orthogonal matrix representation (NOMR). Specifically, the specific individual subspace of each image is estimated and represented uniquely by the sum of a set of basis matrices generated via singular value decomposition (SVD), i.e. the nearest orthogonal matrix (NOM) of original image. Then, the nearest neighbor criterion is introduced for recognition. Compared with the current specific individual subspace based methods (e.g. the sparse representation based classifier, the linear regression based classifier and so on), the proposed NOMR is more robust for alleviating the effect of illumination and heterogeneous (e.g. sketch face recognition), and more intuitive and powerful for handling the small sample size problem. To evaluate the performance of the proposed method, a series of experiments were performed on several face databases: Extended Yale B, CMU-PIE, FRGCv2, AR and CUHK Face Sketch database (CUFS). Experimental results demonstrate that the proposed method achieves encouraging performance compared with the state-of-the-art methods. © 2014 Elsevier B.V.

Keywords:Pattern recognition, Singular value decomposition, Vectors, Image representations, Orthogonal matrix, Singular vectors, Sketch face recognition, Small sample size problems, Sparse representation, State-of-the-art methods, Subspace based methods, Face recognition, Article, automated pattern recognition, computer system, data base, face profile, image analysis, image processing, information processing, intermethod comparison, linear regression analysis, nearest orthogonal matrix representation, singular vector decomposition, validation process, NotOAChecked
Subjects:G Mathematical and Computer Sciences > G440 Human-computer Interaction
Divisions:College of Science > School of Computer Science
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ID Code:20622
Deposited On:26 Mar 2016 19:12

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