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- Publisher Website: 10.1007/978-3-319-14418-4_10
- Scopus: eid_2-s2.0-85078709912
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Book Chapter: Data-driven character animation synthesis
Title | Data-driven character animation synthesis |
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Authors | |
Keywords | Human motion Data-driven animation Character animation Machine learning |
Issue Date | 2018 |
Publisher | Springer. |
Citation | Data-driven character animation synthesis. In Müller, B, Wolf, S (Eds.), Handbook of Human Motion, p. 2003-2031. Cham, Switzerland: Springer, 2018 How to Cite? |
Abstract | In this article, we describe about data-driven character motion synthesis for use mainly on a full-body skeleton structure. Due to the simplicity of capturing motion nowadays, the main issue for animating characters is how to reduce the cost of applying such motion to the characters and how to recycle the motion for interactive motion synthesis. An additional topic of interest is how to convert the style of the movements while preserving the context of the motion. In this article, we primarily cover machine learning techniques that can be useful for such purposes. |
Persistent Identifier | http://hdl.handle.net/10722/288787 |
ISBN |
DC Field | Value | Language |
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dc.contributor.author | Komura, Taku | - |
dc.contributor.author | Habibie, Ikhsanul | - |
dc.contributor.author | Schwarz, Jonathan | - |
dc.contributor.author | Holden, Daniel | - |
dc.date.accessioned | 2020-10-12T08:05:52Z | - |
dc.date.available | 2020-10-12T08:05:52Z | - |
dc.date.issued | 2018 | - |
dc.identifier.citation | Data-driven character animation synthesis. In Müller, B, Wolf, S (Eds.), Handbook of Human Motion, p. 2003-2031. Cham, Switzerland: Springer, 2018 | - |
dc.identifier.isbn | 9783319144177 | - |
dc.identifier.uri | http://hdl.handle.net/10722/288787 | - |
dc.description.abstract | In this article, we describe about data-driven character motion synthesis for use mainly on a full-body skeleton structure. Due to the simplicity of capturing motion nowadays, the main issue for animating characters is how to reduce the cost of applying such motion to the characters and how to recycle the motion for interactive motion synthesis. An additional topic of interest is how to convert the style of the movements while preserving the context of the motion. In this article, we primarily cover machine learning techniques that can be useful for such purposes. | - |
dc.language | eng | - |
dc.publisher | Springer. | - |
dc.relation.ispartof | Handbook of Human Motion | - |
dc.subject | Human motion | - |
dc.subject | Data-driven animation | - |
dc.subject | Character animation | - |
dc.subject | Machine learning | - |
dc.title | Data-driven character animation synthesis | - |
dc.type | Book_Chapter | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1007/978-3-319-14418-4_10 | - |
dc.identifier.scopus | eid_2-s2.0-85078709912 | - |
dc.identifier.spage | 2003 | - |
dc.identifier.epage | 2031 | - |
dc.publisher.place | Cham, Switzerland | - |