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Paper Abstract and Keywords
Presentation 2023-10-27 14:50
User-adaptable Avatar Posture Manipulation
Riku Shinohara (NAIST), Atsushi Hashimoto, Tadashi Kozuno, Shigeo Yoshida (OSX), Yutaro Hirao, Monica Perusquia-Hernandez, Hideaki Uchiyama, Kiyokawa Kiyoshi (NAIST) MVE2023-29
Abstract (in Japanese) (See Japanese page) 
(in English) In this study, we propose a system for acquiring a method of manipulating the avatar posture using the user's hands. In order to manipulate an avatar with different physical characteristics from the hand, a mapping between the joints of the hand and the avatar is required. In conventional methods, this mapping is performed by optimization based on mathematical formulas designed from the viewpoint of biomechanics. However, it is difficult to obtain the optimal operation method for each user with this method. Therefore, we investigate a method to obtain user-optimized avatar operations by using data-based machine learning. An encoder-decoder model is used for machine learning, and user-optimized avatar operations are acquired in two stages: pre-learning and additional learning. For the additional learning, we used a small amount of data obtained from the user's calibration work. We evaluated two types of avatars: a scorpion, for which there is a difference in operation between users, and a frog, for which there is no difference between users. As a result, we found that the proposed model is effective even when there is a difference in operation between users.
Keyword (in Japanese) (See Japanese page) 
(in English) Avatar Manipulation / Hand Avatar / Non-humanoid Avatar / Machine Learning / User Adaptation / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 228, MVE2023-29, pp. 40-45, Oct. 2023.
Paper # MVE2023-29 
Date of Issue 2023-10-19 (MVE) 
ISSN Online edition: ISSN 2432-6380
Copyright
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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 MVE VRSJ-SIG-MR IPSJ-EC HI-SIG-DeMO VRSJ-SIG-CS  
Conference Date 2023-10-26 - 2023-10-27 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To MVE 
Conference Code 2023-10-MVE-SIG-MR-EC-SIG-DeMO-SIG-CS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) User-adaptable Avatar Posture Manipulation 
Sub Title (in English)  
Keyword(1) Avatar Manipulation  
Keyword(2) Hand Avatar  
Keyword(3) Non-humanoid Avatar  
Keyword(4) Machine Learning  
Keyword(5) User Adaptation  
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1st Author's Name Riku Shinohara  
1st Author's Affiliation Nara Institute of Science and Technology (NAIST)
2nd Author's Name Atsushi Hashimoto  
2nd Author's Affiliation OMRON SINIC X Corporation (OSX)
3rd Author's Name Tadashi Kozuno  
3rd Author's Affiliation OMRON SINIC X Corporation (OSX)
4th Author's Name Shigeo Yoshida  
4th Author's Affiliation OMRON SINIC X Corporation (OSX)
5th Author's Name Yutaro Hirao  
5th Author's Affiliation Nara Institute of Science and Technology (NAIST)
6th Author's Name Monica Perusquia-Hernandez  
6th Author's Affiliation Nara Institute of Science and Technology (NAIST)
7th Author's Name Hideaki Uchiyama  
7th Author's Affiliation Nara Institute of Science and Technology (NAIST)
8th Author's Name Kiyokawa Kiyoshi  
8th Author's Affiliation Nara Institute of Science and Technology (NAIST)
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Speaker Author-1 
Date Time 2023-10-27 14:50:00 
Presentation Time 20 minutes 
Registration for MVE 
Paper # MVE2023-29 
Volume (vol) vol.123 
Number (no) no.228 
Page pp.40-45 
#Pages
Date of Issue 2023-10-19 (MVE) 


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