Presentation | 2001/11/10 Acquirement of complex movement patterns in communications Keiichi SUMITA, Yasuhiro WADA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Humans can communicate with complex movements. Some models have been proposed to regenerate complex human movement patterns. However, the focus of these models has been on transformation from movement trajectories to representations and on the regeneration of movements from representations. In other words, the models can not emulate the representation acquirement process with a lot of trial and error like humans. We study a requirement process of complex movement patterns and symbols. In this report, we propose two models, one is a model that estimate the representation of a movement such as via-points, and the other is a model in which an estimated representation is related to a symbol. The first proposed model can acquire a set of via-points to regenerate an original pattern smoothly. We confirm that the second model can connect with some symbols and patterns. We report a summary of models and results from learning experiments. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | communication / complex movement pattern / via point / learning / symbol |
Paper # | HIP2001-63 |
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Committee | HIP |
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Conference Date | 2001/11/10(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Human Information Processing (HIP) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Acquirement of complex movement patterns in communications |
Sub Title (in English) | |
Keyword(1) | communication |
Keyword(2) | complex movement pattern |
Keyword(3) | via point |
Keyword(4) | learning |
Keyword(5) | symbol |
1st Author's Name | Keiichi SUMITA |
1st Author's Affiliation | Nagaoka University of Technology() |
2nd Author's Name | Yasuhiro WADA |
2nd Author's Affiliation | Nagaoka University of Technology |
Date | 2001/11/10 |
Paper # | HIP2001-63 |
Volume (vol) | vol.101 |
Number (no) | 512 |
Page | pp.pp.- |
#Pages | 6 |
Date of Issue |