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Sparse representation frontal facial recognition algorithm based on eigenface
Bo Yang Ding2; Yuan Yan Tang2; Zhen Chao Zhang2; Xue Wei Wang2; Chi Fang1
2013-09-03
Conference Name2013 2nd International Symposium on Electrical & Electronics Engineering (EEESYM 2013)
Source PublicationApplied Mechanics and Materials
Volume347-350
Pages3629-3633
Conference Date2013
Conference PlaceShijiazhuang
Abstract

Face recognition continues to be a hot topic in pattern recognition and computer vision recent years. Meantime, sparse representation is a new technique utilizing compressed sensing method applied in pattern recognition research recent years. This paper comparison with PCA and SP for face recognition, makes some improvement on great performance eigenface algorithm, using sparse representation with eigenface space to achieved better result. Finally, the proposed algorithm based on eigenface sparse recognition shows that of better result. 

KeywordEigenface Principal Component Analysis Recognition Sparse Representation
DOI10.4028/www.scientific.net/AMM.347-350.3629
URLView the original
Indexed By其他
Language英語English
Scopus ID2-s2.0-84883195408
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Document TypeConference paper
CollectionUniversity of Macau
Affiliation1.Department of Electronic Engineering of Tsinghua University,Beijing,100083,China
2.Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Macau, China
First Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
Bo Yang Ding,Yuan Yan Tang,Zhen Chao Zhang,et al. Sparse representation frontal facial recognition algorithm based on eigenface[C], 2013, 3629-3633.
APA Bo Yang Ding., Yuan Yan Tang., Zhen Chao Zhang., Xue Wei Wang., & Chi Fang (2013). Sparse representation frontal facial recognition algorithm based on eigenface. Applied Mechanics and Materials, 347-350, 3629-3633.
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