NDLI: One sample per person face recognition via sparse representation

Content Provider	IET Digital Library
Author	Zhang, Yan Peng, Hua
Abstract	One sample per person face recognition (OSPP) is a challenging problem in face recognition community. Lack of samples leads to performance deterioration. Extended sparse representation-based classifier (ESRC) demonstrates excellent performance on OSPP. However, because there are intra-class variant atoms in the dictionary of ESRC, the number of atoms in the dictionary is always large and it will spend a long time during recognition. In this study, the authors propose a new OSPP face recognition algorithm via sparse representation (OSPP-SR). A compressed dictionary and a new identification strategy are provided in OSPP-SR. It is proved theoretically and experimentally that OSPP-SR reaches better or similar performance but spends less time than ESRC. Experiments are conducted on three different databases (extended Yale Face database B, AR database and FERET database) to show the validity of OSPP-SR. Images under clean and noise conditions are also tested to evaluate the robustness of OSPP-SR.
Starting Page	1126
Ending Page	1134
Page Count	9
ISSN	17519675
Volume Number	10
e-ISSN	17519683
Issue Number	Issue 9, Dec (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/10/9
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2016.0067
Journal	IET Signal Processing
Publisher Date	2016-07-15
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	AR Database Computer Vision And Image Processing Technique ESRC Extended Sparse Representation-based Classifier Extended Yale Face Database Face Recognition FERET Database Image Classification Image Recognition Image Representation One Sample Per Person Face Recognition OSPP Face Recognition Algorithm OSPP-SR Sparse Representation
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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