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Paper Abstract and Keywords
Presentation 2017-11-07 11:00
[Invited Talk] Researches on Impressiveness Multimedia Contents -- Attractiveness Computing using Big Multimedia Data --
Toshihiko Yamasaki (UTokyo) EMM2017-63
Abstract (in Japanese) (See Japanese page) 
(in English) Due to the advancement in machine learning and pattern recognition technologies such as deep neural networks, recognition of “what” has been made very accurate. For instance, object detection and recognition in natural images is a task of understanding “what’s in this picture?” Artificial intelligence developed for Go and Shogi games is also designed for “what’s next?” We believe that understanding “how” and “why” in addition to “what” will be of great importance in the future. For this purpose, understanding humans’ internal state such as sentiment/emotion and intent would also be important.
From this point of view, our research group has been working on impression prediction and analysis of multimedia content. It is believed that impressive contents can be created only by those who are talented and experienced so far. However, our research group has revealed that with enough amount of data, proper labels, and proper machine learning techniques, predicting how impressive the contents are is possible. It is also possible to give feedbacks to creators on how to make the contents more impressive. In my presentation, I would like to introduce some of our representative works such as oral presentation analysis, recognition rate and favorableness score prediction of TV commercials, and so on.
Keyword (in Japanese) (See Japanese page) 
(in English) Big Multimedia Data / Impression Analysis / Machine Learning / Pattern Recognition / Deep Neural Networks / Attractiveness / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 282, EMM2017-63, pp. 45-45, Nov. 2017.
Paper # EMM2017-63 
Date of Issue 2017-10-30 (EMM) 
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 EMM  
Conference Date 2017-11-06 - 2017-11-07 
Place (in Japanese) (See Japanese page) 
Place (in English) Kagoshima Univ. (Inamori Academy) 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Multimedia Fusion, Content Processing, Multimedia Retrieval, Digital Watermarking, and Related Topics 
Paper Information
Registration To EMM 
Conference Code 2017-11-EMM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Researches on Impressiveness Multimedia Contents 
Sub Title (in English) Attractiveness Computing using Big Multimedia Data 
Keyword(1) Big Multimedia Data  
Keyword(2) Impression Analysis  
Keyword(3) Machine Learning  
Keyword(4) Pattern Recognition  
Keyword(5) Deep Neural Networks  
Keyword(6) Attractiveness  
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1st Author's Name Toshihiko Yamasaki  
1st Author's Affiliation The University of Tokyo (UTokyo)
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Speaker Author-1 
Date Time 2017-11-07 11:00:00 
Presentation Time 60 minutes 
Registration for EMM 
Paper # EMM2017-63 
Volume (vol) vol.117 
Number (no) no.282 
Page p.45 
#Pages
Date of Issue 2017-10-30 (EMM) 


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