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Paper Abstract and Keywords
Presentation 2020-10-10 10:30
Analysis and Classification of Gestures in TED Talks
Hitoshi Teshima (Kyushu Univ.), Naoki Wake (Microsoft), Diego Thomas (Kyushu Univ.), Yuta Nakashima (Osaka Univ.), Hiroshi Kawasaki (Kyushu Univ.), Katsushi Ikeuchi (Microsoft) PRMU2020-35
Abstract (in Japanese) (See Japanese page) 
(in English) Most of automatic gesture generation methods have focused on generating beat gestures only. Among these methods, many generate gestures from audio data, but only a few consider text data as additional input to generate meaningful gestures. Our intuition is that text data contains many semantic information that is strongly correlated to the type of gesture that people use in their speech. Using text data is therefore a powerful way to generate many kind of gestures and mimic human behavior. To enable such gesture generation, a large amount of data with annotated gesture type labels on the video is essential to investigate the correlation between text and gestures. In this paper, we propose a new method to automatically detect and classify the gestures of a speaker and their types from a video with text data. We study speech data from TED Talks and introduce a new dataset with annotated gestures. We classify the gestures into three categories: Imagistic Gesture that complements the content of the text, Beat Gesture that has nothing to do with the content of the text, and Deictic Gesture that points to something.
Keyword (in Japanese) (See Japanese page) 
(in English) Gesture Classification / Gesture Generation / Gesture Data / / / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 187, PRMU2020-35, pp. 104-109, Oct. 2020.
Paper # PRMU2020-35 
Date of Issue 2020-10-02 (PRMU) 
ISSN Online edition: ISSN 2432-6380
Copyright
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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)
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Conference Information
Committee PRMU  
Conference Date 2020-10-09 - 2020-10-10 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Recognition and understating of human 
Paper Information
Registration To PRMU 
Conference Code 2020-10-PRMU 
Language English (Japanese title is available) 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Analysis and Classification of Gestures in TED Talks 
Sub Title (in English)  
Keyword(1) Gesture Classification  
Keyword(2) Gesture Generation  
Keyword(3) Gesture Data  
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1st Author's Name Hitoshi Teshima  
1st Author's Affiliation Kyushu University (Kyushu Univ.)
2nd Author's Name Naoki Wake  
2nd Author's Affiliation Microsoft (Microsoft)
3rd Author's Name Diego Thomas  
3rd Author's Affiliation Kyushu University (Kyushu Univ.)
4th Author's Name Yuta Nakashima  
4th Author's Affiliation Osaka University (Osaka Univ.)
5th Author's Name Hiroshi Kawasaki  
5th Author's Affiliation Kyushu University (Kyushu Univ.)
6th Author's Name Katsushi Ikeuchi  
6th Author's Affiliation Microsoft (Microsoft)
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Date Time 2020-10-10 10:30:00 
Presentation Time 15 minutes 
Registration for PRMU 
Paper # PRMU2020-35 
Volume (vol) vol.120 
Number (no) no.187 
Page pp.104-109 
#Pages
Date of Issue 2020-10-02 (PRMU) 


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