@techreport{oai:ipsj.ixsq.nii.ac.jp:00220302,
 author = {木村, 文哉 and 宍戸, 英彦 and 北原, 格 and Fumiya, Kimura and Hidehiko, Shishido and Itaru, Kitahara},
 issue = {38},
 month = {Sep},
 note = {This research aims to generate 4D portrait of a person that can be playback over a long time period. 4D portrait is a free-viewpoint video of a person with temporal changes in facial expression. In our proposed method, the parameters that represent facial expressions and head poses of a person are obtained from a video captured by a monocular RGB camera with continuously changing the viewpoint. Then, a neural radiance field (NeRF) is trained from the captured video and estimated parameters. Using this radiance field, 4D portrait is generated based on the similarity of the person's facial expressions. This paper describes a method for determining transition frames based on facial expression similarity to enable long playback., This research aims to generate 4D portrait of a person that can be playback over a long time period. 4D portrait is a free-viewpoint video of a person with temporal changes in facial expression. In our proposed method, the parameters that represent facial expressions and head poses of a person are obtained from a video captured by a monocular RGB camera with continuously changing the viewpoint. Then, a neural radiance field (NeRF) is trained from the captured video and estimated parameters. Using this radiance field, 4D portrait is generated based on the similarity of the person's facial expressions. This paper describes a method for determining transition frames based on facial expression similarity to enable long playback.},
 title = {ニューラル場表現と表情類似度に基づく4次元ポートレート生成法},
 year = {2022}
}