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Article: Local motion phases for learning multi-contact character movements
Title | Local motion phases for learning multi-contact character movements |
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Authors | |
Keywords | human motion character control character animation neural networks deep learning character interactions |
Issue Date | 2020 |
Citation | ACM Transactions on Graphics, 2020, v. 39, n. 4, article no. 54 How to Cite? |
Abstract | © 2020 ACM. Training a bipedal character to play basketball and interact with objects, or a quadruped character to move in various locomotion modes, are difficult tasks due to the fast and complex contacts happening during the motion. In this paper, we propose a novel framework to learn fast and dynamic character interactions that involve multiple contacts between the body and an object, another character and the environment, from a rich, unstructured motion capture database. We use one-on-one basketball play and character interactions with the environment as examples. To achieve this task, we propose a novel feature called local motion phase, that can help neural networks to learn asynchronous movements of each bone and its interaction with external objects such as a ball or an environment. We also propose a novel generative scheme to reproduce a wide variation of movements from abstract control signals given by a gamepad, which can be useful for changing the style of the motion under the same context. Our scheme is useful for animating contact-rich, complex interactions for real-time applications such as computer games. |
Persistent Identifier | http://hdl.handle.net/10722/288830 |
ISSN | 2023 Impact Factor: 7.8 2023 SCImago Journal Rankings: 7.766 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Starke, Sebastian | - |
dc.contributor.author | Zhao, Yiwei | - |
dc.contributor.author | Komura, Taku | - |
dc.contributor.author | Zaman, Kazi | - |
dc.date.accessioned | 2020-10-12T08:05:59Z | - |
dc.date.available | 2020-10-12T08:05:59Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | ACM Transactions on Graphics, 2020, v. 39, n. 4, article no. 54 | - |
dc.identifier.issn | 0730-0301 | - |
dc.identifier.uri | http://hdl.handle.net/10722/288830 | - |
dc.description.abstract | © 2020 ACM. Training a bipedal character to play basketball and interact with objects, or a quadruped character to move in various locomotion modes, are difficult tasks due to the fast and complex contacts happening during the motion. In this paper, we propose a novel framework to learn fast and dynamic character interactions that involve multiple contacts between the body and an object, another character and the environment, from a rich, unstructured motion capture database. We use one-on-one basketball play and character interactions with the environment as examples. To achieve this task, we propose a novel feature called local motion phase, that can help neural networks to learn asynchronous movements of each bone and its interaction with external objects such as a ball or an environment. We also propose a novel generative scheme to reproduce a wide variation of movements from abstract control signals given by a gamepad, which can be useful for changing the style of the motion under the same context. Our scheme is useful for animating contact-rich, complex interactions for real-time applications such as computer games. | - |
dc.language | eng | - |
dc.relation.ispartof | ACM Transactions on Graphics | - |
dc.subject | human motion | - |
dc.subject | character control | - |
dc.subject | character animation | - |
dc.subject | neural networks | - |
dc.subject | deep learning | - |
dc.subject | character interactions | - |
dc.title | Local motion phases for learning multi-contact character movements | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1145/3386569.3392450 | - |
dc.identifier.scopus | eid_2-s2.0-85090397346 | - |
dc.identifier.hkuros | 325512 | - |
dc.identifier.volume | 39 | - |
dc.identifier.issue | 4 | - |
dc.identifier.spage | article no. 54 | - |
dc.identifier.epage | article no. 54 | - |
dc.identifier.eissn | 1557-7368 | - |
dc.identifier.isi | WOS:000583700300027 | - |
dc.identifier.issnl | 0730-0301 | - |