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Paper Abstract and Keywords
Presentation 2017-10-12 15:00
A Study of a Liveness Detection Method Using Fully Convolutional Network for Face Recognition Systems
Koichi Ito, Takehisa Okano, Takafumi Aoki (Tohoku Univ.) BioX2017-27
Abstract (in Japanese) (See Japanese page) 
(in English) A face recognition system may accept a malicious person by presenting a printed photo of a user. To address this problem, liveness detection which classifies an input image into real and fake accesses is required for face recognition systems. Feature descriptors for liveness detection cannot be designed manually, since it is difficult for a human to classify an input image into real and fake accesses. Therefore, deep learning approaches are recently used to develop a liveness detection method for face recognition systems. A Fully Convolutional Network (FCN), which is one of convolutional neural networks, is used for pixel-by-pixel semantic segmentation of images. This paper investigates a liveness detection method using FCN for face recognition.
Keyword (in Japanese) (See Japanese page) 
(in English) liveness detection / spoofing / face recognition / biometrics / security / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 236, BioX2017-27, pp. 11-15, Oct. 2017.
Paper # BioX2017-27 
Date of Issue 2017-10-05 (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)
Download PDF BioX2017-27

Conference Information
Committee BioX  
Conference Date 2017-10-12 - 2017-10-13 
Place (in Japanese) (See Japanese page) 
Place (in English) Nobumoto Ohama Memorial Hall 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Biometrics, etc. 
Paper Information
Registration To BioX 
Conference Code 2017-10-BioX 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study of a Liveness Detection Method Using Fully Convolutional Network for Face Recognition Systems 
Sub Title (in English)  
Keyword(1) liveness detection  
Keyword(2) spoofing  
Keyword(3) face recognition  
Keyword(4) biometrics  
Keyword(5) security  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Koichi Ito  
1st Author's Affiliation Tohoku University (Tohoku Univ.)
2nd Author's Name Takehisa Okano  
2nd Author's Affiliation Tohoku University (Tohoku Univ.)
3rd Author's Name Takafumi Aoki  
3rd Author's Affiliation Tohoku University (Tohoku Univ.)
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Speaker Author-1 
Date Time 2017-10-12 15:00:00 
Presentation Time 25 minutes 
Registration for BioX 
Paper # BioX2017-27 
Volume (vol) vol.117 
Number (no) no.236 
Page pp.11-15 
#Pages 5 
Date of Issue 2017-10-05 (BioX) 

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