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Paper Abstract and Keywords
Presentation 2026-03-18 10:20
Emotion Estimation While Viewing VR Advertising Images Using Multimodal Features Including Text Information
Maki Kubo, Wataru Kameyama (Waseda Univ.) CQ2025-124
Abstract (in Japanese) (See Japanese page) 
(in English) This paper aims for providing more effective VR advertisements, and examines emotion estimation for VR advertisements using bio-signals acquired during advertisement viewing, together with advertisement features and individual preferences. In our previous studies, the emotion has been estimated by using bio-signals, physical features of images and genre of advertisements. In this paper, to further improve the estimation accuracy for unseen advertisements, word occurrence frequencies and sentiment scores extracted from advertisement texts are newly introduced as additional features. Experimental results show that integrating word occurrence frequencies with conventional features achieves the highest estimation accuracy. Furthermore, binary classification results exceed much the chance level. Feature importance analysis reveals that effective features differ across emotion categories, indicating the effectiveness of multimodal information integration for VR advertisement recommendation.
Keyword (in Japanese) (See Japanese page) 
(in English) Bio-signals / Multimodal Features / VR Advertisement / Emotion Estimation / / / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 409, CQ2025-124, pp. 133-138, March 2026.
Paper # CQ2025-124 
Date of Issue 2026-03-09 (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 CQ2025-124

Conference Information
Committee CQ MVE IMQ IE  
Conference Date 2026-03-16 - 2026-03-18 
Place (in Japanese) (See Japanese page) 
Place (in English) Okinawa-Sangyoushien-Center 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To CQ 
Conference Code 2026-03-CQ-MVE-IMQ-IE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Emotion Estimation While Viewing VR Advertising Images Using Multimodal Features Including Text Information 
Sub Title (in English)  
Keyword(1) Bio-signals  
Keyword(2) Multimodal Features  
Keyword(3) VR Advertisement  
Keyword(4) Emotion Estimation  
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1st Author's Name Maki Kubo  
1st Author's Affiliation Waseda University (Waseda Univ.)
2nd Author's Name Wataru Kameyama  
2nd Author's Affiliation Waseda University (Waseda Univ.)
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Speaker Author-1 
Date Time 2026-03-18 10:20:00 
Presentation Time 20 minutes 
Registration for CQ 
Paper # CQ2025-124 
Volume (vol) vol.125 
Number (no) no.409 
Page pp.133-138 
#Pages 6 
Date of Issue 2026-03-09 (CQ) 

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