A study of synthesizing new human motions from sampled motions using Tensor Decomposition

Rovshan Kalanov*, Jieun Cho, Jun Ohya

*この研究の対応する著者

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

This paper applies an algorithm, based on Tensor Decomposition, to a new synthesis application: by using sampled motions of people of different ages under different emotional states, new motions for other people are synthesized. Human motion is the composite consequence of multiple elements, including the action performed and a motion signature that captures the distinctive pattern of movement of a particular individual. By performing decomposition, based on N-mode SVD (singular value decomposition), the algorithm analyzes motion data spanning multiple subjects performing different actions to extract these motion elements. The analysis yields a generative motion model that can synthesize new motions in the distinctive styles of these individuals. The effectiveness of applying the tensor decomposition approach to our purpose was confirmed by synthesizing novel walking motions for a person by using the extracted signature.

本文言語English
ホスト出版物のタイトルIEEE International Conference on Multimedia and Expo, ICME 2005
ページ1326-1329
ページ数4
DOI
出版ステータスPublished - 2005 12 1
イベントIEEE International Conference on Multimedia and Expo, ICME 2005 - Amsterdam, Netherlands
継続期間: 2005 7 62005 7 8

出版物シリーズ

名前IEEE International Conference on Multimedia and Expo, ICME 2005
2005

Conference

ConferenceIEEE International Conference on Multimedia and Expo, ICME 2005
国/地域Netherlands
CityAmsterdam
Period05/7/605/7/8

ASJC Scopus subject areas

  • 工学(全般)

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