@techreport{oai:ipsj.ixsq.nii.ac.jp:00209814,
 author = {佐藤, 荘一朗 and 青野, 雅樹 and Soichiro, Sato and Masaki, Aono},
 issue = {16},
 month = {Feb},
 note = {本論文では，姿勢推定モデルに基づくスポーツ動画の動作分類について述べる．具体的には，PoseNet を用いて 17 種類の人間の骨格の推定座標を出力し，推定座標の推移を表現した特徴量を導入した．これに加えて，骨格の推定座標に基づく動画フレームのクロップを行ったものを従来モデルを拡張した幾つかの DNN モデルへの入力に使用した．この姿勢推定モデルに基づく動作分類のための提案手法を MediaEval2020 Sports Video Classification タスクで提供されたデータに適用した．, In this paper, we propose a motion classification method of sports videos based on a posture estimation model. Specifically, we introduced features to estimate the coordinates of 17 types of human skeletons, representing the transition of the estimated coordinates, which in turn were generated by PoseNet. In addition to this, we cropped the video frames based on the estimated coordinates of the skeleton were used as input to several DNN models that extended the conventional models. The proposed method for motion classification based on this posture estimation model was applied to the data provided by the MediaEval2020 Sports Video Classification task.},
 title = {姿勢推定モデルに基づくスポーツ動画の動作分類},
 year = {2021}
}