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 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) |
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PRMU2020-35 |
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) |
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Keyword(1) |
Gesture Classification |
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Gesture Generation |
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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 |
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Kyushu University (Kyushu Univ.) |
6th Author's Name |
Katsushi Ikeuchi |
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Microsoft (Microsoft) |
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Speaker |
Author-1 |
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 |
6 |
Date of Issue |
2020-10-02 (PRMU) |
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