Gabor-based region covariance matrices for face recognition

Yanwei Pang; Yuan Yuan; Xuelong Li

doi:10.1109/TCSVT.2008.924108

Gabor-based region covariance matrices for face recognition

Yanwei Pang, Yuan Yuan, Xuelong Li

科研成果: 期刊稿件 › 文章 › 同行评审

265 引用（Scopus）

摘要

This paper presents a new method for human face recognition by utilizing Gabor-based region covariance matrices as face descriptors. Both pixel locations and Gabor coefficients are employed to form the covariance matrices. Experimental results demonstrate the advantages of this proposed method.

源语言	英语
文章编号	4498432
页（从-至）	989-993
页数	5
期刊	IEEE Transactions on Circuits and Systems for Video Technology
卷	18
期	7
DOI	https://doi.org/10.1109/TCSVT.2008.924108
出版状态	已出版 - 7月 2008
已对外发布	是

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10.1109/TCSVT.2008.924108

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title = "Gabor-based region covariance matrices for face recognition",

abstract = "This paper presents a new method for human face recognition by utilizing Gabor-based region covariance matrices as face descriptors. Both pixel locations and Gabor coefficients are employed to form the covariance matrices. Experimental results demonstrate the advantages of this proposed method.",

keywords = "Biometrics, Face recognition, Gabor, Region covariance matrix (RCM)",

author = "Yanwei Pang and Yuan Yuan and Xuelong Li",

year = "2008",

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T1 - Gabor-based region covariance matrices for face recognition

AU - Pang, Yanwei

AU - Yuan, Yuan

AU - Li, Xuelong

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AB - This paper presents a new method for human face recognition by utilizing Gabor-based region covariance matrices as face descriptors. Both pixel locations and Gabor coefficients are employed to form the covariance matrices. Experimental results demonstrate the advantages of this proposed method.

KW - Biometrics

KW - Face recognition

KW - Gabor

KW - Region covariance matrix (RCM)

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U2 - 10.1109/TCSVT.2008.924108

DO - 10.1109/TCSVT.2008.924108

M3 - 文章

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SN - 1051-8215

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JO - IEEE Transactions on Circuits and Systems for Video Technology

JF - IEEE Transactions on Circuits and Systems for Video Technology

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Gabor-based region covariance matrices for face recognition

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