Strategy diagram for identifying play strategies in multi-view soccer video data

Yukihiro Nakamura, Shin Ando, Kenji Aoki, Hiroyuki Mano, Einoshin Suzuki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


In this paper, we propose a strategy diagram to acquire knowledge of soccer for identifying play strategies in multi-view video data. Soccer, as the most popular team sport in the world, attracts attention of researchers in knowledge discovery and data mining and its related areas. Domain knowledge is mandatory in such applications but acquiring domain knowledge of soccer from experts is a laborious task. Moreover such domain knowledge is typically acquired and used in an ad-hoc manner. Diagrams in textbooks can be considered as a promising source of knowledge and are intuitive to humans. Our strategy diagram enables a systematic acquisition and use of such diagrams as domain knowledge for identifying play strategies in video data of a soccer game taken from multiple angles. The key idea is to transform multi-view video data to sequential coordinates then match the strategy diagram in terms of essential features. Experiments using video data of a national tournament for high school students show that the proposed method exhibits promising results and gives insightful lessons for further studies.

Original languageEnglish
Title of host publicationDiscovery Science - 9th International Conference, DS 2006, Proceedings
PublisherSpringer Verlag
Number of pages12
ISBN (Print)3540464913, 9783540464914
Publication statusPublished - 2006
Event9th International Conference on Discovery Science, DS 2006 - Barcelona, Spain
Duration: Oct 7 2006Oct 10 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4265 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other9th International Conference on Discovery Science, DS 2006

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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