TY - GEN
T1 - Strategy diagram for identifying play strategies in multi-view soccer video data
AU - Nakamura, Yukihiro
AU - Ando, Shin
AU - Aoki, Kenji
AU - Mano, Hiroyuki
AU - Suzuki, Einoshin
PY - 2006/1/1
Y1 - 2006/1/1
N2 - 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.
AB - 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.
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UR - http://www.scopus.com/inward/citedby.url?scp=33750728454&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:33750728454
SN - 3540464913
SN - 9783540464914
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 173
EP - 184
BT - Discovery Science - 9th International Conference, DS 2006, Proceedings
PB - Springer Verlag
T2 - 9th International Conference on Discovery Science, DS 2006
Y2 - 7 October 2006 through 10 October 2006
ER -