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Paper Abstract and Keywords
Presentation 2021-02-18 17:05
A Note on Prediction of Important Scenes in Baseball Videos via Multimodal Variational Autoencoder Using Tweets and Videos
Kaito Hirasawa, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) This paper presents a prediction method of important scenes in baseball videos based on multimodal variational autoencoder (MVAE). Tweets posted on Twitter by viewers while viewing baseball games include the content of the games and the opinions of the viewers. Then we construct a method for high-quality prediction of important scenes based on MVAE which can consider the relationships between textual, visual and audio features extracted tweets and videos. The proposed method newly introduces the important scene predictor which predicts the probability of the scene being important from the latent features calculated from these features. Finally, this paper shows the effectiveness of the proposed method through experiments using actual baseball videos and tweets.
Keyword (in Japanese) (See Japanese page) 
(in English) Sports video analysis / Twitter analysis / prediction of important scenes / multimodal analysis / / / /  
Reference Info. ITE Tech. Rep., vol. 45, no. 4, ME2021-14, pp. 71-75, Feb. 2021.
Paper # ME2021-14 
Date of Issue 2021-02-11 (MMS, ME, AIT) 
ISSN Print edition: ISSN 1342-6893  Online edition: ISSN 2424-1970
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Conference Information
Conference Date 2021-02-18 - 2021-02-19 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Image Processing, etc. 
Paper Information
Registration To ME 
Conference Code 2021-02-IE-ITS-MMS-ME-AIT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Note on Prediction of Important Scenes in Baseball Videos via Multimodal Variational Autoencoder Using Tweets and Videos 
Sub Title (in English)  
Keyword(1) Sports video analysis  
Keyword(2) Twitter analysis  
Keyword(3) prediction of important scenes  
Keyword(4) multimodal analysis  
1st Author's Name Kaito Hirasawa  
1st Author's Affiliation Hokkaido University (Hokkaido Univ.)
2nd Author's Name Keisuke Maeda  
2nd Author's Affiliation Hokkaido University (Hokkaido Univ.)
3rd Author's Name Takahiro Ogawa  
3rd Author's Affiliation Hokkaido University (Hokkaido Univ.)
4th Author's Name Miki Haseyama  
4th Author's Affiliation Hokkaido University (Hokkaido Univ.)
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Date Time 2021-02-18 17:05:00 
Presentation Time 25 
Registration for ME 
Paper # ITE-MMS2021-14,ITE-ME2021-14,ITE-AIT2021-14 
Volume (vol) ITE-45 
Number (no) no.4 
Page pp.71-75 
#Pages ITE-5 
Date of Issue ITE-MMS-2021-02-11,ITE-ME-2021-02-11,ITE-AIT-2021-02-11 

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