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Improving cross-modal face recognition using polarimetric imaging

用测定偏振的成像的改善跨 modal 脸识别

作     者:Short, Nathaniel Hu, Shuowen Gurram, Prudhvi Gurton, Kristan Chan, Alex 

作者机构:US Army Res Lab Adelphi MD 20783 USA Booz Allen & Hamilton Inc Mclean VA 22102 USA MBO Partners Herndon VA 20171 USA 

出 版 物:《OPTICS LETTERS》 (光学快报)

年 卷 期:2015年第40卷第6期

页      面:882-885页

核心收录:

学科分类:070207[理学-光学] 07[理学] 08[工学] 0803[工学-光学工程] 0702[理学-物理学] 

主  题:Infrared Pattern recognition Imaging systems Polarimetric imaging 

摘      要:We investigate the performance of polarimetric imaging in the long-wave infrared (LWIR) spectrum for cross-modal face recognition. For this work, polarimetric imagery is generated as stacks of three components: the conventional thermal intensity image (referred to as S-0), and the two Stokes images, S-1 and S-2, which contain combinations of different polarizations. The proposed face recognition algorithm extracts and combines local gradient magnitude and orientation information from S-0, S-1, and S-2 to generate a robust feature set that is well-suited for cross-modal face recognition. Initial results show that polarimetric LWIR-to-visible face recognition achieves an 18% increase in Rank-1 identification rate compared to conventional LWIR-to-visible face recognition. We conclude that a substantial improvement in automatic face recognition performance can be achieved by exploiting the polarization-state of radiance, as compared to using conventional thermal imagery. (C) 2015 Optical Society of America

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