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Paper Abstract and Keywords
Presentation 2022-09-13 14:00
Study on eye tracking based skill level estimation for assisting collaborative work
Ryohei Saijo, Hiromu Miyashita, Shohei Matsuo (NTT) LOIS2022-11 IE2022-33 EMM2022-39
Abstract (in Japanese) (See Japanese page) 
(in English) In collaborative work among multiple workers with different skill levels, communication discrepancies may occur due to differences in the skill level of the workers. Such discrepancies in communication lead to a deterioration in the efficiency and quality of work. This study aims to eliminate such discrepancies by presenting supplementary information to users during work according to their skill level. This paper first studied a method for estimating skill level based on collected gaze data during work on the Tsume-Shogi (Japanese chess) task performed in a VR space. The results suggest that it is possible to discriminate skilled from unskilled players using a model learned by SVM by extracting gaze data during the first 3 seconds of response to the task. It advanced the development of the skill level estimation method for assisting collaborative work.
Keyword (in Japanese) (See Japanese page) 
(in English) eye tracking / skill level estimation / assisting cooperative work / VR / tsume shougi(japanese chess) / mind-to-mind communications / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 177, LOIS2022-11, pp. 7-12, Sept. 2022.
Paper # LOIS2022-11 
Date of Issue 2022-09-06 (LOIS, IE, EMM) 
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 LOIS2022-11 IE2022-33 EMM2022-39

Conference Information
Committee ITE-ME EMM IE LOIS IEE-CMN IPSJ-AVM  
Conference Date 2022-09-13 - 2022-09-14 
Place (in Japanese) (See Japanese page) 
Place (in English) Keio Univ. Yagami Campus (Hybrid) 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To LOIS 
Conference Code 2022-09-ME-EMM-IE-LOIS-CMN-AVM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Study on eye tracking based skill level estimation for assisting collaborative work 
Sub Title (in English)  
Keyword(1) eye tracking  
Keyword(2) skill level estimation  
Keyword(3) assisting cooperative work  
Keyword(4) VR  
Keyword(5) tsume shougi(japanese chess)  
Keyword(6) mind-to-mind communications  
Keyword(7)  
Keyword(8)  
1st Author's Name Ryohei Saijo  
1st Author's Affiliation NTT Digital Twin Computing Research Center, Nippon Telegraph and Telephone Corporation (NTT)
2nd Author's Name Hiromu Miyashita  
2nd Author's Affiliation NTT Digital Twin Computing Research Center, Nippon Telegraph and Telephone Corporation (NTT)
3rd Author's Name Shohei Matsuo  
3rd Author's Affiliation NTT Digital Twin Computing Research Center, Nippon Telegraph and Telephone Corporation (NTT)
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Speaker Author-1 
Date Time 2022-09-13 14:00:00 
Presentation Time 20 minutes 
Registration for LOIS 
Paper # LOIS2022-11, IE2022-33, EMM2022-39 
Volume (vol) vol.122 
Number (no) no.177(LOIS), no.178(IE), no.179(EMM) 
Page pp.7-12 
#Pages 6 
Date of Issue 2022-09-06 (LOIS, IE, EMM) 

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