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Paper Abstract and Keywords
Presentation 2019-03-18 10:45
ADL Recognition based on Movement Trajectory of Hand and Object Recognition using Deep Learning for Self-Support
Hiroki Kojima (OIT), Sho Ooi (Rits), Mutsuo Sano (OIT) BioX2018-51 PRMU2018-155
Abstract (in Japanese) (See Japanese page) 
(in English) In our laboratory, we have been studying cognitive rehabilitation for patients with acquired brain injury and dementia based on activities daily living (ADL) such as cooking and clearing. We proposed a method of cleaning behavior estimation using deep learning and conducted experiments of cleaning behavior to patients with acquired brain injury. Specifically, we estimated cleaning behavior using cleaning tools and cleaning area (person's direction). Cleaning tools are recognized by YOLO algorithm, person's directions are recognized by OpenPose algorithm. However, in this method, there were many misrecognition. Therefore, we add movement trajectory of object and hand as feature and describe recognition accuracy of ADL behavior. As a result, accuracy was improved by a method of error correction method which considers time continuity when features are face orientation, hand movement, and object movement.
Keyword (in Japanese) (See Japanese page) 
(in English) ADL / Self Support / YOLO / OpenPose / Living Behavior Recognition / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 513, PRMU2018-155, pp. 131-136, March 2019.
Paper # PRMU2018-155 
Date of Issue 2019-03-10 (BioX, PRMU) 
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 BioX2018-51 PRMU2018-155

Conference Information
Committee PRMU BioX  
Conference Date 2019-03-17 - 2019-03-18 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To PRMU 
Conference Code 2019-03-PRMU-BioX 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) ADL Recognition based on Movement Trajectory of Hand and Object Recognition using Deep Learning for Self-Support 
Sub Title (in English)  
Keyword(1) ADL  
Keyword(2) Self Support  
Keyword(3) YOLO  
Keyword(4) OpenPose  
Keyword(5) Living Behavior Recognition  
Keyword(6)  
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1st Author's Name Hiroki Kojima  
1st Author's Affiliation Graduate School of Osaka Institute of Technology (OIT)
2nd Author's Name Sho Ooi  
2nd Author's Affiliation Ritsumeikan University (Rits)
3rd Author's Name Mutsuo Sano  
3rd Author's Affiliation Osaka Institute of Technology (OIT)
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Speaker Author-1 
Date Time 2019-03-18 10:45:00 
Presentation Time 15 minutes 
Registration for PRMU 
Paper # BioX2018-51, PRMU2018-155 
Volume (vol) vol.118 
Number (no) no.512(BioX), no.513(PRMU) 
Page pp.131-136 
#Pages 6 
Date of Issue 2019-03-10 (BioX, PRMU) 

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