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Paper Abstract and Keywords
Presentation 2018-03-03 14:25
Study of Visual Cognition Estimation based on Gaze Movements and target Visual Cognition Difficultly
Hideho Sakaguchi (NAIST/ATR), Akira Utsumi (ATR), Kenji Susami (ATR/Kindai Univ.), Tadahisa Kondo (Kogakuin Univ.), Masayuki Kanbara (NAIST/ATR), Norihiro Hagita (ATR/NAIST) HIP2017-96
Abstract (in Japanese) (See Japanese page) 
(in English) Proper estimation of human visual awareness is significant to realize an efficient support for visual tasks such as vehicle driving. We examine a method to estimate occurrences of human visual cognition. Several methods based on gaze movement have been proposed to estimate human visual awareness where simple thresholding rules on target-gaze angles are employed. However, those methods take no account of the variety of target visual appearances. In our previous studies, we clarified the relationship between gaze behavior in visual search tasks and the target’s VCDs (Visual Cognition Difficulties) defined as performance values on visual search tasks for a particular target. In this paper, we evaluate the estimation performance by using machine-learning based implementation. The results suggest the improvement of performance for visual cognition estimation by considering the target’s VCDs.
Keyword (in Japanese) (See Japanese page) 
(in English) gaze movements / Visual Cognition Difficultly / machine learning / Convolutional Neural Network (CNN) / / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 470, HIP2017-96, pp. 17-20, March 2018.
Paper # HIP2017-96 
Date of Issue 2018-02-24 (HIP) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
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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)
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Conference Information
Committee HIP ASJ-H  
Conference Date 2018-03-03 - 2018-03-04 
Place (in Japanese) (See Japanese page) 
Place (in English) IT Souzoukan, Naha City 
Topics (in Japanese) (See Japanese page) 
Topics (in English) VR Psychology, Human Information Processing, Physiological Acoustics, Speech, Acoustics in general 
Paper Information
Registration To HIP 
Conference Code 2018-03-HIP-H 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Study of Visual Cognition Estimation based on Gaze Movements and target Visual Cognition Difficultly 
Sub Title (in English)  
Keyword(1) gaze movements  
Keyword(2) Visual Cognition Difficultly  
Keyword(3) machine learning  
Keyword(4) Convolutional Neural Network (CNN)  
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1st Author's Name Hideho Sakaguchi  
1st Author's Affiliation Nara Institute of Science and Technology/Advanced Telecommunications Research Institute International (NAIST/ATR)
2nd Author's Name Akira Utsumi  
2nd Author's Affiliation Advanced Telecommunications Research Institute International (ATR)
3rd Author's Name Kenji Susami  
3rd Author's Affiliation Advanced Telecommunications Research Institute International/Kindai University (ATR/Kindai Univ.)
4th Author's Name Tadahisa Kondo  
4th Author's Affiliation Kogakuin University (Kogakuin Univ.)
5th Author's Name Masayuki Kanbara  
5th Author's Affiliation Nara Institute of Science and Technology/Advanced Telecommunications Research Institute International (NAIST/ATR)
6th Author's Name Norihiro Hagita  
6th Author's Affiliation Advanced Telecommunications Research Institute International/Nara Institute of Science and Technology (ATR/NAIST)
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Speaker Author-1 
Date Time 2018-03-03 14:25:00 
Presentation Time 25 minutes 
Registration for HIP 
Paper # HIP2017-96 
Volume (vol) vol.117 
Number (no) no.470 
Page pp.17-20 
#Pages
Date of Issue 2018-02-24 (HIP) 


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