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ファイル | 記述 | サイズ | フォーマット | |
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transinf.2019edp7180.pdf | 3.3 MB | Adobe PDF | 見る/開く |
タイトル: | Integration of Experts' and Beginners' Machine Operation Experiences to Obtain a Detailed Task Model |
著者: | CHEN, Longfei NAKAMURA, Yuichi KONDO, Kazuaki DAMEN, Dima MAYOL-CUEVAS, Walterio |
著者名の別形: | 中村, 裕一 近藤, 一晃 |
キーワード: | egocentric vision hotspots gaze dynamic alignment task modeling operation difficulty |
発行日: | Jan-2021 |
出版者: | Institute of Electronics, Information and Communications Engineers (IEICE) |
誌名: | IEICE Transactions on Information and Systems |
巻: | E104.D |
号: | 1 |
開始ページ: | 152 |
終了ページ: | 161 |
抄録: | We propose a novel framework for integrating beginners' machine operational experiences with those of experts' to obtain a detailed task model. Beginners can provide valuable information for operation guidance and task design; for example, from the operations that are easy or difficult for them, the mistakes they make, and the strategy they tend to choose. However, beginners' experiences often vary widely and are difficult to integrate directly. Thus, we consider an operational experience as a sequence of hand-machine interactions at hotspots. Then, a few experts' experiences and a sufficient number of beginners' experiences are unified using two aggregation steps that align and integrate sequences of interactions. We applied our method to more than 40 experiences of a sewing task. The results demonstrate good potential for modeling and obtaining important properties of the task. |
著作権等: | ©2020 THe Institute of Electronics, Information and Communications Engineers |
URI: | http://hdl.handle.net/2433/262917 |
DOI(出版社版): | 10.1587/transinf.2019edp7180 |
出現コレクション: | 学術雑誌掲載論文等 |
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