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 and 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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BioX2018-3 |
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) |
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Keyword(1) |
Biometrics |
Keyword(2) |
verification score |
Keyword(3) |
generative model |
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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 |
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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 |
6 |
Date of Issue |
2018-05-17 (BioX) |
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