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dc.contributor.authorLi, Guoyuan
dc.contributor.authorMao, Runze
dc.contributor.authorHildre, Hans Petter
dc.contributor.authorZhang, Houxiang
dc.date.accessioned2019-10-16T07:11:58Z
dc.date.available2019-10-16T07:11:58Z
dc.date.created2019-10-15T10:45:37Z
dc.date.issued2019
dc.identifier.issn1551-3203
dc.identifier.urihttp://hdl.handle.net/11250/2622421
dc.description.abstractImproving the training programs for maritime operations is beneficial to enhance maritime safety in practice. In this paper, we propose a novel approach to the assessment of visual attention in a maritime operation so as to support an expert-in-the-loop training program. Experts' knowledge of maritime operation and experiences in the simulator are incorporated into the training program in three ways. First, through a questionnaire, information about task division, identification of critical operation, and definitions of areas of interest (AOIs) is incorporated as prior knowledge for modeling visual attention. Second, a weight scale factor that emphasizes the high importance of visual focus in critical operations is utilized to generate an operations-dependent attention map. Third, based on an expert's attention map and visual switch between AOIs, a similarity metric is designed as a comprehensive evaluation between saliency and visual transition. A case study of heavy lifting operation is performed by two groups of trainees who have received different briefings about “critical operation”. The assessment result shows the group with more detailed briefing obtains a 6% similarity score higher than the other group, which is consistent with the debriefing result of a superior performance of that group. The proposed approach is thus verified effective in assessing visual attention for the expert-in-the-loop training program.nb_NO
dc.language.isoengnb_NO
dc.publisherIEEEnb_NO
dc.titleVisual Attention Assessment for Expert-in-the-loop Training in a Maritime Operation Simulatornb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionacceptedVersionnb_NO
dc.source.journalIEEE Transactions on Industrial Informaticsnb_NO
dc.identifier.doi10.1109/TII.2019.2945361
dc.identifier.cristin1737125
dc.relation.projectNorges forskningsråd: 280703nb_NO
dc.relation.projectNorges forskningsråd: 237929nb_NO
dc.description.localcode© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.nb_NO
cristin.unitcode194,64,93,0
cristin.unitnameInstitutt for havromsoperasjoner og byggteknikk
cristin.ispublishedfalse
cristin.fulltextpostprint
cristin.qualitycode2


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