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Title: Integration of Experts' and Beginners' Machine Operation Experiences to Obtain a Detailed Task Model
Authors: CHEN, Longfei
NAKAMURA, Yuichi  kyouindb  KAKEN_id
KONDO, Kazuaki
DAMEN, Dima
MAYOL-CUEVAS, Walterio
Author's alias: 中村, 裕一
近藤, 一晃
Keywords: egocentric vision
hotspots
gaze
dynamic alignment
task modeling
operation difficulty
Issue Date: Jan-2021
Publisher: Institute of Electronics, Information and Communications Engineers (IEICE)
Journal title: IEICE Transactions on Information and Systems
Volume: E104.D
Issue: 1
Start page: 152
End page: 161
Abstract: 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.
Rights: ©2020 THe Institute of Electronics, Information and Communications Engineers
URI: http://hdl.handle.net/2433/262917
DOI(Published Version): 10.1587/transinf.2019edp7180
Appears in Collections:Journal Articles

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