We propose a method for detecting biased-highlights in a broadcast sports video according to viewers' attributes obtained from a large number of tweets. Recently, Twitter is widely used to make real-time play-by-play comments on TV programs, especially on sports games. This trend enables us to effectively acquire the viewers' interests in a large mass. In order to make use of such tweets for highlight detection in broadcast sports video, the proposed method first performs an attribute analysis on the set of tweets issued by each user to classify which team he/she supports. It then detects biased-highlights by referring to the number of tweets made by viewers with a specific attribute. © Springer-Verlag 2013.
CITATION STYLE
Kobayashi, T., Takahashi, T., Deguchi, D., Ide, I., & Murase, H. (2013). Detection of biased broadcast sports video highlights by attribute-based tweets analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7733 LNCS, pp. 364–373). https://doi.org/10.1007/978-3-642-35728-2_35
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