Near infrared face recognition: A literature survey

被引:24
作者
Farokhi, Sajad [1 ,2 ]
Flusser, Jan [1 ]
Sheikh, Usman Ullah [3 ]
机构
[1] Acad Sci Czech Republ, Inst Informat Theory & Automat, CR-18208 Prague 8, Czech Republic
[2] Islamic Azad Univ, Najafabad Branch, Fac Comp Engn, Najafabad 8514143131, Iran
[3] Univ Teknol Malaysia, Fac Elect Engn, Digital Signal & Image Proc Res Grp, Johor Baharu 81310, Malaysia
关键词
Literature survey; Biometrics; Face recognition; Near infrared; Illumination invariant;
D O I
10.1016/j.cosrev.2016.05.003
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
As a primary modality in biometrics, human face recognition has been employed widely in the computer vision domain because of its performance in a wide range of applications such as surveillance systems and forensics. Recently, near infrared (NIR) imagery has been used in many face recognition systems because of the high robustness to illumination changes in the acquired images. Even though some surveys have been conducted in this infrared domain, they have focused on thermal infrared methods rather than NIR methods. Furthermore, none of the previous infrared surveys provided comprehensive and critical analyses of NIR methods. Therefore, this paper presents an up-to-date survey of the well-known NIR methods that are used to solve the problem of illumination. The paper includes a discussion of the benefits and drawbacks of various NIR methods. Finally, the most promising avenues for future research are highlighted. (C) 2016 Elsevier Inc. All rights reserved.
引用
收藏
页码:1 / 17
页数:17
相关论文
共 125 条
[1]  
Abas Khairul Hamimah, 2010, American Journal of Applied Sciences, V7, P283, DOI 10.3844/ajassp.2010.283.289
[2]   Face description with local binary patterns:: Application to face recognition [J].
Ahonen, Timo ;
Hadid, Abdenour ;
Pietikainen, Matti .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2006, 28 (12) :2037-2041
[3]   State of the art in infrared face recognition [J].
Akhloufi, Moulay ;
Bendada, Abdelhakim ;
Batsale, Jean-Christophe .
QUANTITATIVE INFRARED THERMOGRAPHY JOURNAL, 2008, 5 (01) :3-26
[4]   Face recognition by independent component analysis [J].
Bartlett, MS ;
Movellan, JR ;
Sejnowski, TJ .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 2002, 13 (06) :1450-1464
[5]   Face recognition by fusing thermal infrared and visible imagery [J].
Bebis, George ;
Gyaourova, Aglika ;
Singh, Saurabh ;
Pavlidis, Ioannis .
IMAGE AND VISION COMPUTING, 2006, 24 (07) :727-742
[6]   Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection [J].
Belhumeur, PN ;
Hespanha, JP ;
Kriegman, DJ .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1997, 19 (07) :711-720
[7]   Factors that influence algorithm performance in the Face Recognition Grand Challenge [J].
Beveridge, J. Ross ;
Givens, Geof H. ;
Phillips, P. Jonathon ;
Draper, Bruce A. .
COMPUTER VISION AND IMAGE UNDERSTANDING, 2009, 113 (06) :750-762
[8]   Face recognition based on fitting a 3D morphable model [J].
Blanz, V ;
Vetter, T .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2003, 25 (09) :1063-1074
[9]  
Bledsoe WW, 1966, MODEL METHOD FACIAL
[10]  
Bowyer Kevin W., 2004, INT C PATT REC ICPR, P358