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Paper Abstract and Keywords
Presentation 2021-03-03 15:55
A Consideration on Estimation Accuracy Improvement of Unlearned Data in Video Viewer's Emotion Estimation Using Bio-signals
Misato Matsumura, Mutsumi Suganuma, Wataru Kameyama (Waseda Univ.) CQ2020-120
Abstract (in Japanese) (See Japanese page) 
(in English) We are conducting a research of video viewer’s emotion estimation from bio-signals using deep neural network in order to utilize it for video recommendation systems. In our previous results, the estimation accuracy of unlearned data is low, and it is considered that the number of training data is insufficient. So, the improvement of emotion estimation accuracy of unlearned data remains as an issue. Therefore, in this paper, we conduct an experiment using more videos and estimate emotions using more training data. As the result, the emotion estimation accuracy of unlearned data improves in 8 out of 9 subjects. We also consider how to determine the emotion labels, and find that the difficulty of the estimation seems to differ depending on the emotions. From these results, it is suggested that it is necessary to set up more appropriate emotion labels and to obtain a lot of training data in order to improve the emotion estimation accuracy of unlearned data.
Keyword (in Japanese) (See Japanese page) 
(in English) Bio-signals / Video Viewer / Emotion Estimation / Unlearned Data / Deep Neural Network / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 392, CQ2020-120, pp. 67-72, March 2021.
Paper # CQ2020-120 
Date of Issue 2021-02-22 (CQ) 
ISSN 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 CQ2020-120

Conference Information
Committee MVE IMQ IE CQ  
Conference Date 2021-03-01 - 2021-03-03 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To CQ 
Conference Code 2021-03-MVE-IMQ-IE-CQ 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Consideration on Estimation Accuracy Improvement of Unlearned Data in Video Viewer's Emotion Estimation Using Bio-signals 
Sub Title (in English)  
Keyword(1) Bio-signals  
Keyword(2) Video Viewer  
Keyword(3) Emotion Estimation  
Keyword(4) Unlearned Data  
Keyword(5) Deep Neural Network  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Misato Matsumura  
1st Author's Affiliation Waseda University (Waseda Univ.)
2nd Author's Name Mutsumi Suganuma  
2nd Author's Affiliation Waseda University (Waseda Univ.)
3rd Author's Name Wataru Kameyama  
3rd Author's Affiliation Waseda University (Waseda Univ.)
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Speaker Author-1 
Date Time 2021-03-03 15:55:00 
Presentation Time 25 minutes 
Registration for CQ 
Paper # CQ2020-120 
Volume (vol) vol.120 
Number (no) no.392 
Page pp.67-72 
#Pages 6 
Date of Issue 2021-02-22 (CQ) 

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