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霊長類における身体動作時系列の分節構造推定
https://repo.qst.go.jp/records/78219
https://repo.qst.go.jp/records/7821957349cd3-3941-4c1d-82d0-da888681a09f
| Item type | 会議発表用資料 / Presentation(1) | |||||
|---|---|---|---|---|---|---|
| 公開日 | 2019-12-24 | |||||
| タイトル | ||||||
| タイトル | 霊長類における身体動作時系列の分節構造推定 | |||||
| 言語 | ||||||
| 言語 | jpn | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_c94f | |||||
| 資源タイプ | conference object | |||||
| アクセス権 | ||||||
| アクセス権 | metadata only access | |||||
| アクセス権URI | http://purl.org/coar/access_right/c_14cb | |||||
| 著者 |
三村, 喬生
× 三村, 喬生× 中村, 友昭× 松本, 惇平× 西条, 寿夫× 須原, 哲也× 持橋, 大地× 南本, 敬史× Mimura, Koki× Suhara, Tetsuya× Minamimoto, Takafumi |
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| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | Understanding the nature of nonverbal communication (eye contacts, face expressions, body postures, hand gestures, body motions, etc...) is one of the core issue in behavioral neuroscience. In this study, we demonstrated the data-driven dynamical segmentation of the body expressions in free moving small non-human primate, common marmoset. We developed a new marker-less 3D motion tracking system optimized to marmoset. Then, we proposed unsupervised segmentation using a Gaussian process-hidden semi-Markov model (GP-HSMM). As a result, we succeeded to classify three types of marmoset feeding behavior (high position feeding, low position feeding, and low position feeding with hands) only based on body parts positions, face direction, and body angle information. This result suggested that proposing system could represent high versatility to quantify the animal nonverbal body expressions without qualitative teacher labels. | |||||
| 会議概要（会議名, 開催地, 会期, 主催者等） | ||||||
| 内容記述タイプ | Other | |||||
| 内容記述 | 2019年度人工知能学会全国大会 | |||||
| 発表年月日 | ||||||
| 日付 | 2019-06-04 | |||||
| 日付タイプ | Issued | |||||
