@techreport{oai:ipsj.ixsq.nii.ac.jp:00220301,
 author = {逸見, 勲 and 宍戸, 英彦 and 北原, 格 and Isao, Hemmi and Hidehiko, Shishido and Itaru, Kitahara},
 issue = {37},
 month = {Sep},
 note = {The quality of the video is greatly affected by the camerawork. Unlike filming a movie, it is hard to reshoot live entertainment. Therefore, it is more important to consider the camerawork based on the information obtained in advance. The methods to generate camerawork using scenarios have been proposed, however, the methods have not considered changes in the standing positions of the performers on the stage yet. This study proposes an automatic camera work generation method that uses deep learning to output camera positions and postures for each scene based on the standing positions of the performers in each scene (keyframe) obtained from the stage script., The quality of the video is greatly affected by the camerawork. Unlike filming a movie, it is hard to reshoot live entertainment. Therefore, it is more important to consider the camerawork based on the information obtained in advance. The methods to generate camerawork using scenarios have been proposed, however, the methods have not considered changes in the standing positions of the performers on the stage yet. This study proposes an automatic camera work generation method that uses deep learning to output camera positions and postures for each scene based on the standing positions of the performers in each scene (keyframe) obtained from the stage script.},
 title = {パフォーマンス撮影のための演者立ち位置情報を基にしたカメラ位置姿勢生成手法},
 year = {2022}
}