Presentation 2016-12-09
Play Estimation Based on Player's View in American Football
Hana Miwa, Yasuhiko Kitamura,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Play estimation in previous research has been based on the movement of all the players in the field, which estimates a play chosen by the opponent team in american football. However, it is difficult for players to watch the movement of all the players during a play in real games. In this paper, we propose a method to estimate a play by using support vector machine based on the data from a limited view of each player. The estimation accuracy decreases as the view narrowness increases, and that of players in the back is better than in the front. In some cases, it can be improved by combinig the results of multiple players.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) american football / play estimation / support vector machine
Paper # AI2016-15
Date of Issue 2016-12-02 (AI)

Conference Information
Committee AI
Conference Date 2016/12/9(1days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Toshiharu Sugawara(Waseda Univ.)
Vice Chair Tsunenori Mine(Kyushu Univ.) / Daisuke Katagami(Tokyo Polytechnic Univ.)
Secretary Tsunenori Mine(Ritsumeikan Univ.) / Daisuke Katagami(Shizuoka Univ.)
Assistant Yuichi Sei(Univ. of Electro-Comm.)

Paper Information
Registration To Technical Committee on Artificial Intelligence and Knowledge-Based Processing
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Play Estimation Based on Player's View in American Football
Sub Title (in English)
Keyword(1) american football
Keyword(2) play estimation
Keyword(3) support vector machine
1st Author's Name Hana Miwa
1st Author's Affiliation Kwansei Gakuin University(Kwansei Gakuin Univ.)
2nd Author's Name Yasuhiko Kitamura
2nd Author's Affiliation Kwansei Gakuin University(Kwansei Gakuin Univ.)
Date 2016-12-09
Paper # AI2016-15
Volume (vol) vol.116
Number (no) AI-350
Page pp.pp.17-22(AI),
#Pages 6
Date of Issue 2016-12-02 (AI)