書誌事項
- タイトル別名
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- Estimating Whole Body Motion from Partially Observed Body Motion During Walking
抄録
<p>Measurement of whole body motion using motion capture play important role in fields of rehabilitation, imitation learning, and human-robot interaction. However, the measurement requires a large number of markers and sensors to be worn and there are many limitation on the measurement environment. In this paper, we propose a novel method to estimate whole body motion from partially observed body motion during walking. We create a deep neural network similar to the Convolutional Neural Network (CNN) auto-encoder to extract features of walking motion from partial motion data and estimate whole body motion from the features. In the experiment, we compare the estimated joint angles and motion data to verify the usefulness of the proposed method. </p>
収録刊行物
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- シンポジウム: スポーツ・アンド・ヒューマン・ダイナミクス講演論文集
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シンポジウム: スポーツ・アンド・ヒューマン・ダイナミクス講演論文集 2018 (0), A-13-, 2018
一般社団法人 日本機械学会
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詳細情報 詳細情報について
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- CRID
- 1390282763116020352
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- NII論文ID
- 130007654333
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- ISSN
- 24329509
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- Crossref
- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可