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Paper Abstract and Keywords
Presentation 2021-03-02 09:50
Improving an Accuracy of Personal Identification Using Ensemble Learning and Footsteps
Yoshiki Goto, Akitoshi Itai (Chubu Univ.) BioX2020-41 CNR2020-14
Abstract (in Japanese) (See Japanese page) 
(in English) It is known that the footstep includes personal characteristics. We often recognize a person from walking footsteps in limited situation. If the high accuracy personal identification using footstep is possible, a novel surveillance system like a crime prevention system, or a biometric system are expected. We showed that the ResNet of CNN trained by footstep waveform images performs the identification accuracy of 95.8% for 10 subjects. Pan reported that the footstep identification using 7 steps of vibration data and ITSVM with the accuracy of 96.0% for 10 subjects.
However, the accuracy of these researches is not enough to use of a biometric system.
In this paper, we propose a high time resolution dataset. In addition, we apply an ensemble learning using three datasets to achieve more accurate personal identification.
Keyword (in Japanese) (See Japanese page) 
(in English) Footstep / Ensemble learning / CNN / Personal identification / / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 393, BioX2020-41, pp. 7-11, March 2021.
Paper # BioX2020-41 
Date of Issue 2021-02-23 (BioX, CNR) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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 BioX2020-41 CNR2020-14

Conference Information
Committee BioX CNR  
Conference Date 2021-03-02 - 2021-03-02 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To BioX 
Conference Code 2021-03-BioX-CNR 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Improving an Accuracy of Personal Identification Using Ensemble Learning and Footsteps 
Sub Title (in English)  
Keyword(1) Footstep  
Keyword(2) Ensemble learning  
Keyword(3) CNN  
Keyword(4) Personal identification  
1st Author's Name Yoshiki Goto  
1st Author's Affiliation Chubu University (Chubu Univ.)
2nd Author's Name Akitoshi Itai  
2nd Author's Affiliation Chubu University (Chubu Univ.)
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Speaker Author-1 
Date Time 2021-03-02 09:50:00 
Presentation Time 20 minutes 
Registration for BioX 
Paper # BioX2020-41, CNR2020-14 
Volume (vol) vol.120 
Number (no) no.393(BioX), no.394(CNR) 
Page pp.7-11 
Date of Issue 2021-02-23 (BioX, CNR) 

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