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Paper Abstract and Keywords
Presentation 2023-11-05 15:05
Investigation of Effective Features for Estimating Agreement or Disagreement by Facial images in Online Conferences
Hiroki Saito, Kyotaro Sato, Junji Yamato (Kogakuin Univ.) CNR2023-15 HCS2023-77
Abstract (in Japanese) (See Japanese page) 
(in English) In online conferences, it is more difficult to capture detailed facial expression changes than in offline conferences. In addition, it is difficult to convey the intentions of the participants. In this study, we investigate effective features f or estimating agreement and disagreement using facial images. We confirm whether grouping people with similar facial expression changes is effective in estimating agreement or disagreement by grouping people with similar facial expression changes and comparing the resul ts with those without grouping. As a result of feature selection based on feature importance using XGBoost, the estimation accuracy was improved by making individual binary classifiers for groups prone to changes around the eyes and groups prone to changes around the mouth, rather than making a binary classifier using all the data without grouping.
Keyword (in Japanese) (See Japanese page) 
(in English) Online Conferences / Agreement / Disagreement / Facial expression recognition / / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 241, CNR2023-15, pp. 45-49, Nov. 2023.
Paper # CNR2023-15 
Date of Issue 2023-10-29 (CNR, HCS) 
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 CNR2023-15 HCS2023-77

Conference Information
Committee HCS CNR  
Conference Date 2023-11-05 - 2023-11-06 
Place (in Japanese) (See Japanese page) 
Place (in English) Kogakuin University 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Communication and Interaction of Human, Robot, and Agent, etc. 
Paper Information
Registration To CNR 
Conference Code 2023-11-HCS-CNR 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Investigation of Effective Features for Estimating Agreement or Disagreement by Facial images in Online Conferences 
Sub Title (in English)  
Keyword(1) Online Conferences  
Keyword(2) Agreement  
Keyword(3) Disagreement  
Keyword(4) Facial expression recognition  
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1st Author's Name Hiroki Saito  
1st Author's Affiliation Kogakuin University (Kogakuin Univ.)
2nd Author's Name Kyotaro Sato  
2nd Author's Affiliation Kogakuin University (Kogakuin Univ.)
3rd Author's Name Junji Yamato  
3rd Author's Affiliation Kogakuin University (Kogakuin Univ.)
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Speaker Author-1 
Date Time 2023-11-05 15:05:00 
Presentation Time 25 minutes 
Registration for CNR 
Paper # CNR2023-15, HCS2023-77 
Volume (vol) vol.123 
Number (no) no.241(CNR), no.242(HCS) 
Page pp.45-49 
#Pages 5 
Date of Issue 2023-10-29 (CNR, HCS) 

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