イクノ　ソウイチロウ   Soichiro Ikuno   生野　壮一郎    所属   コンピュータサイエンス学部 コンピュータサイエンス学科    職種   教授
言語種別	英語
発行・発表の年月	2021/12
形態種別	国際会議論文
査読	査読あり
標題	Motion Feature Extraction and Stylization for Character Animation using Hilbert-Huang Transform
執筆形態	共著
掲載誌名	Proceedings of the 2021 ACM International Conference on Intelligent Computing and its Emerging Applications
掲載区分	国外
出版社・発行元	ACM
巻・号・頁	pp.16-21
総ページ数	6
著者・共著者	Ran Dong, Yangfei Lin, Qiong Chang, Junpei Zhong, Dongsheng Cai, and Soichiro Ikuno
概要	This paper presents novel insights to feature extraction and stylization of character motion in the instantaneous frequency domain by proposing a method using the Hilbert-Huang transform (HHT). HHT decomposes human motion capture data in the frequency domain into several pseudo monochromatic signals, so-called intrinsic mode functions (IMFs). We propose an algorithm to reconstruct these IMFs and extract motion features automatically using the Fibonacci sequence in the link-dynamical structure of the human body. Our research revealed that these reconstructed motions could be mainly divided into three parts, a primary motion and a secondary motion, corresponding to the animation principles, and a basic motion consisting of posture and position. Our method help animators edit target motions by extracting and blending the primary or secondary motions extracted from a source motion. To demonstrate results, we applied our proposed method to general motions (jumping, punching, and walking motions) to achieve different stylizations.