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Paper Abstract and Keywords
Presentation 2018-03-08 14:35
Accuracy Evaluation of Machine Learning-based Human Anomaly Motion Recognition using Human Pose Estimation
Kengo Ichihara, Masaru Takeuchi, Kenji Kanai, Jiro Katto (Waseda Univ.) IMQ2017-41 IE2017-133 MVE2017-83
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we evaluate recognition accuracy of human motion by using a state-of-the-art pose estimation method called “OpenPose”. We construct 3D character models as a training data by using 3D modeling software and train the data by using Support Vector Model (SVM), Neural Network (NN), Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN). Evaluation results indicate that NN provides the highest recognition accuracy among all methods in case of using our data set. In addition, especially in CNN case, we validate that not only use of the image, but also use of temporal information will contribute to accuracy improvement.
Keyword (in Japanese) (See Japanese page) 
(in English) Pose estimation / Machine learning / Action recognition / / / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 484, IE2017-133, pp. 89-94, March 2018.
Paper # IE2017-133 
Date of Issue 2018-03-01 (IMQ, IE, MVE) 
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 IMQ2017-41 IE2017-133 MVE2017-83

Conference Information
Committee CQ MVE IE IMQ  
Conference Date 2018-03-08 - 2018-03-09 
Place (in Japanese) (See Japanese page) 
Place (in English) Okinawa Industry Support Center 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Five Senses Media, Cooking and Eating Activities Media, Multimedia, Media Experience, Video Encoding, Image Media Quality, Network Quality and Reliability, etc. (Co-sponsor: Technical Committee on Multimedia on Cooking and Eating Activities (CEA)) 
Paper Information
Registration To IE 
Conference Code 2018-03-CQ-MVE-IE-IMQ 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Accuracy Evaluation of Machine Learning-based Human Anomaly Motion Recognition using Human Pose Estimation 
Sub Title (in English)  
Keyword(1) Pose estimation  
Keyword(2) Machine learning  
Keyword(3) Action recognition  
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1st Author's Name Kengo Ichihara  
1st Author's Affiliation Waseda University (Waseda Univ.)
2nd Author's Name Masaru Takeuchi  
2nd Author's Affiliation Waseda University (Waseda Univ.)
3rd Author's Name Kenji Kanai  
3rd Author's Affiliation Waseda University (Waseda Univ.)
4th Author's Name Jiro Katto  
4th Author's Affiliation Waseda University (Waseda Univ.)
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Speaker Author-1 
Date Time 2018-03-08 14:35:00 
Presentation Time 25 minutes 
Registration for IE 
Paper # IMQ2017-41, IE2017-133, MVE2017-83 
Volume (vol) vol.117 
Number (no) no.483(IMQ), no.484(IE), no.485(MVE) 
Page pp.89-94 
#Pages 6 
Date of Issue 2018-03-01 (IMQ, IE, MVE) 

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