Automatic live sport video streams curation system from user generated media

Kazuki Fujisawa, Yuko Hirabe, Hirohiko Suwa, Yutaka Arakawa, Keiichi Yasumoto

研究成果: 書籍/レポート タイプへの寄稿

抄録

Emerging Internet of Things (IoT) technologies will allow spectators in a sport game to produce various video streams from various angles. With existing technologies, however, it is difficult to process massive and various data streams for multi-channel contents in real-time. To solve this problem, we aim to construct a software agent (called "Curator") that compiles video contents automatically according to his/ her values. In this paper, we propose a system to automatically switch multiple video streams that general sports spectators have taken using Random Forests classifier. Meta data such as image feature data and game progress data is extracted for each video scene as the input of the classifier. For evaluation, we constructed a camera switching timing estimation model using the live TV broadcast of some baseball game data. A video of another baseball game was curated with the constructed model. As a result, our system predicted the camera switching timing with accuracy (F-measure) of 85.3% on weighted average for the base camera work and 99.7% for the fixed camera work.

本文言語英語
ホスト出版物のタイトルSports Media, Marketing, and Management
ホスト出版物のサブタイトルBreakthroughs in Research and Practice
出版社IGI Global
ページ417-435
ページ数19
ISBN(電子版)9781522554769
ISBN(印刷版)1522554750, 9781522554752
DOI
出版ステータス出版済み - 3月 2 2018
外部発表はい

!!!All Science Journal Classification (ASJC) codes

  • 経済学、計量経済学および金融学(全般)
  • ビジネス、管理および会計(全般)

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