@article{oai:ipsj.ixsq.nii.ac.jp:00207382,
 author = {伊藤, 慶明 and 小嶋, 和徳 and 千葉, 康汰 and 林, 慶亮 and Yoshiaki, Itoh and Kazunori, Kojima and Kouta, Chiba and Keisuke, Hayashi},
 issue = {1},
 journal = {情報処理学会論文誌デジタルプラクティス（TDP）},
 month = {Oct},
 note = {サッカーの試合においてPK（ペナルティーキック）は勝敗を左右することが多く，ゴールキーパーがPKを阻止することは重要であるが，PKでゴールキーパーがシュートを阻止できる確率は低い．そこで本論文ではまず，ボールが蹴られる前のシュート動作の骨格点データを取得し左右の蹴り分けの自動判別を機械学習し，キック方向の自動予測を行う．次に，キッカーが蹴る直前にキック方向を予測するための着目すべき重要特徴点を分析する．さらに，実際のフィールド実験の結果，ゴールキーパーがその重要特徴点に着目することで予測精度が向上し，提案法の有効性を検証できた．, This paper first investigates key points for predicting a kick direction in penalty kicks in football games. Kinect V2 is used for extracting features of a kicker. The kick direction is trained and automatically predicted by a support vector machine. Experiments were conducted and two key points for predicting a kick direction are identified. Field experiments were then conducted for soccer players who belonged to a soccer club in their high school. The results showed the prediction accuracy of goal keepers improved after key points were told. The results were thought to be limited to the players.},
 pages = {1--7},
 title = {ペナルティーキックの自動方向予測における重要特徴点とゴールキーパーの予測精度向上},
 volume = {1},
 year = {2020}
}