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A Near-infrared Image Based Face Recognition System
University of Southampton,UK April 10-April 12
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/FGR.2006.13Seventh IEEE International Conference ...
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Stan Z. Li, Lun Zhang, ShengCai Liao, XiangXin Zhu, RuFeng Chu, Meng Ao, Ran He, "A Near-infrared Image Based Face Recognition System," Automatic Face and Gesture Recognition, IEEE International Conference on, pp. 455-460, Seventh IEEE International Conference on Automatic Face and Gesture Recognition (FG'06), 2006.
 
 
BibTex
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@article{ 10.1109/FGR.2006.13,
author = {Stan Z. Li and Lun Zhang and ShengCai Liao and XiangXin Zhu and RuFeng Chu and Meng Ao and Ran He},
title = {A Near-infrared Image Based Face Recognition System},
journal ={Automatic Face and Gesture Recognition, IEEE International Conference on},
volume = {0},
year = {2006},
isbn = {0-7695-2503-2},
pages = {455-460},
doi = {http://doi.ieeecomputersociety.org/10.1109/FGR.2006.13},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Automatic Face and Gesture Recognition, IEEE International Conference on
TI - A Near-infrared Image Based Face Recognition System
SN - 0-7695-2503-2
SP455
EP460
A1 - Stan Z. Li,
A1 - Lun Zhang,
A1 - ShengCai Liao,
A1 - XiangXin Zhu,
A1 - RuFeng Chu,
A1 - Meng Ao,
A1 - Ran He,
PY - 2006
KW - null
VL - 0
JA - Automatic Face and Gesture Recognition, IEEE International Conference on
ER -
 
Stan Z. Li, Chinese Academy of Sciences, China
Lun Zhang, Chinese Academy of Sciences, China
ShengCai Liao, Chinese Academy of Sciences, China
XiangXin Zhu, Chinese Academy of Sciences, China
RuFeng Chu, Chinese Academy of Sciences, China
Meng Ao, Chinese Academy of Sciences, China
Ran He, Chinese Academy of Sciences, China
In this paper, we present a near infrared (NIR) image based face recognition system. Firstly, we describe a design of NIR image capture device which minimizes influence of environmental lighting on face images. Both face and facial feature localization and face recognition are performed using local features with AdaBoost learning. An evaluation in real-world user scenario shows that the system achieves excellent accuracy, speed and usability.
Citation:
Stan Z. Li, Lun Zhang, ShengCai Liao, XiangXin Zhu, RuFeng Chu, Meng Ao, Ran He, "A Near-infrared Image Based Face Recognition System," fg, pp.455-460, Seventh IEEE International Conference on Automatic Face and Gesture Recognition (FG'06), 2006
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