Gaze-Aware Cognitive Assistant for Multiscreen Surveillance
Hodgetts, Helen M.
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Surveillance operators must scan multiple camera feeds to ensure timely detection of incidents; however, variability in scanning behavior can lead to untimely/failed detection of critical information in feeds that were neglected for a long period. Us-ing an eye tracker to monitor screen fixations we can calculate (in real-time) the time elapsed since the last scan of each particular feed, allowing the setting-up of targeted countermeasures contingent on operator oculomotor behavior. One ave-nue is to provide operators with timely alerts to modulate the scan pattern to avoid attentional tunneling and inattentional blindness. We test such an adaptive solution within a major event surveillance simulation and preliminary results show that operator scan behavior can be modulated, although further investigation is re-quired to determine warning frequency and modality to optimize the balance be-tween saliency and workload increase. Future work will focus on adding a real-time vigilance detection and countermeasure capability.
Advances in Intelligent Systems and Computing;Vol 722
Tremblay S., Lafond D., Chamberland C., Hodgetts H.M., Vachon F. (2018) 'Gaze-Aware Cognitive Assistant for Multiscreen Surveillance', In: Karwowski W., Ahram T. (eds) Intelligent Human Systems Integration. IHSI 2018. Advances in Intelligent Systems and Computing, 722, pp.230-236 . DOI: https://doi.org/10.1007/978-3-319-73888-8_36
Dynodwr Gwrthrych Digidol (DOI)https://doi.org/10.1007/978-3-319-73888-8_36
This paper was published in Advances in Intelligent Systems and Computing on 31 December 2017 (online) available at https://doi.org/10.1007/978-3-319-73888-8_36
Cardiff Metropolitan University (Grant ID: Cardiff Metropolian (Internal))