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Paper Abstract and Keywords
Presentation 2018-05-24 15:45
A probabilistic verification method using multi-feature for environment-robust biometrics
Hidetsugu Uchida, Narishige Abe, Shigefumi Yamada (FUJITSU LAB.) BioX2018-3
Abstract (in Japanese) (See Japanese page) 
(in English) This paper reports a probabilistic verification method using multi-feature for environment-robust biometrics. In biometrics, verification is performed by comparing features which are extracted to contain individuality from biometric information such as face images. However, as well as individuality, those features contain undesired information derived from environmental variations where biometric information is captured. The undesired information is mixed the feature as distortions and degrades verification performance. Toward to environment-robust verification, probabilistic linear discriminative analysis (PLDA)-based verification has been studied. PLDA models individuality space and environment space with large learning data and can perform verification referring both of twospaceinwhole. Inthispaper, PLDAisextendedtodealwithtwokindsoffeaturesextractedfromonebiometric information simultaneously. This proposed model can model individuality space and environment space with the two kinds of features. In results of experiments using face images, the proposed model is superior to conventional PLDA.
Keyword (in Japanese) (See Japanese page) 
(in English) Biometrics / verification score / generative model / probabilistic linear discriminative analysis / probabilistic canonical correlation analysis / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 55, BioX2018-3, pp. 21-26, May 2018.
Paper # BioX2018-3 
Date of Issue 2018-05-17 (BioX) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
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reproduction
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
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Conference Information
Committee BioX ITE-ME ITE-IST  
Conference Date 2018-05-24 - 2018-05-25 
Place (in Japanese) (See Japanese page) 
Place (in English) Kanazawa Univ. Nishimachi Satelite Plaza 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Biometrics, etc. 
Paper Information
Registration To BioX 
Conference Code 2018-05-BioX-ME-IST 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A probabilistic verification method using multi-feature for environment-robust biometrics 
Sub Title (in English)  
Keyword(1) Biometrics  
Keyword(2) verification score  
Keyword(3) generative model  
Keyword(4) probabilistic linear discriminative analysis  
Keyword(5) probabilistic canonical correlation analysis  
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1st Author's Name Hidetsugu Uchida  
1st Author's Affiliation FUJITSU LABORATORIES LTD. (FUJITSU LAB.)
2nd Author's Name Narishige Abe  
2nd Author's Affiliation FUJITSU LABORATORIES LTD. (FUJITSU LAB.)
3rd Author's Name Shigefumi Yamada  
3rd Author's Affiliation FUJITSU LABORATORIES LTD. (FUJITSU LAB.)
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Speaker Author-1 
Date Time 2018-05-24 15:45:00 
Presentation Time 30 minutes 
Registration for BioX 
Paper # BioX2018-3 
Volume (vol) vol.118 
Number (no) no.55 
Page pp.21-26 
#Pages
Date of Issue 2018-05-17 (BioX) 


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