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Paper Abstract and Keywords
Presentation 2024-03-01 15:20
On Using Existing Facial Expression Recognition Model for Student Behavior Tracking
Yuna Kaneko, Masato Kikuchi, Tadachika Ozono (NIT) AI2023-43
Abstract (in Japanese) (See Japanese page) 
(in English) It is challenging for teachers to understand students' reactions during online lectures. Estimating student behaviors by facial expression recognition is proposed, but further studies are needed.
These approaches utilize general facial expression recognition models. However, students' facial expressions during lectures are too weak to recognize, and a micro-facial expression recognition model is required to correspond to the facial expressions during lectures. Therefore, we have collected a lecture-specific facial expression dataset through a simulated lecture experiment.
In this paper, we use the collected dataset to examine the applicability of existing models for facial expression recognition in lectures. Specifically, we review the facial expression recognition models and datasets and discuss how to use emotion labels, considering existing studies.
Keyword (in Japanese) (See Japanese page) 
(in English) Facial Expression Recognition Model / Micro-expressions / Student Behavior Tracking / / / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 405, AI2023-43, pp. 37-40, March 2024.
Paper # AI2023-43 
Date of Issue 2024-02-23 (AI) 
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 AI2023-43

Conference Information
Committee AI  
Conference Date 2024-03-01 - 2024-03-01 
Place (in Japanese) (See Japanese page) 
Place (in English) Room0221, Bldg.2-C, Nagoya Institute of Technology 
Topics (in Japanese) (See Japanese page) 
Topics (in English) SMASH24 Winter Symposium 
Paper Information
Registration To AI 
Conference Code 2024-03-AI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) On Using Existing Facial Expression Recognition Model for Student Behavior Tracking 
Sub Title (in English)  
Keyword(1) Facial Expression Recognition Model  
Keyword(2) Micro-expressions  
Keyword(3) Student Behavior Tracking  
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1st Author's Name Yuna Kaneko  
1st Author's Affiliation Nagoya Institute of Technology (NIT)
2nd Author's Name Masato Kikuchi  
2nd Author's Affiliation Nagoya Institute of Technology (NIT)
3rd Author's Name Tadachika Ozono  
3rd Author's Affiliation Nagoya Institute of Technology (NIT)
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Speaker Author-1 
Date Time 2024-03-01 15:20:00 
Presentation Time 20 minutes 
Registration for AI 
Paper # AI2023-43 
Volume (vol) vol.123 
Number (no) no.405 
Page pp.37-40 
#Pages 4 
Date of Issue 2024-02-23 (AI) 

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