The complex visual search involved in baggage screening requires operators to determine quickly whether a bag contains threatening objects that are embedded in a high degree of visual clutter. Methods for calculating visual clutter have been developed, and research has demonstrated the negative impact of clutter on search performance. The current study examined whether leveraging visual clutter information on the display during search could improve baggage screening performance above and beyond the conventional screening process. Ninety undergraduates searched x-ray images of bags for weapon items in a low fidelity baggage screening simulation; two clutter-based preview conditions displayed a limited portion of the bag to the participant before the entire bag was displayed. Eye movement data confirmed that the preview process guided the participant's attention to the corresponding previewed region. However, analysis of the baggage screening performance data showed there were no significant benefits associated with either clutter-based preview conditions compared with a control condition in which the entire bag was displayed for the duration of the trial. Thus, the results suggest that using clutter-based preview to guide visual attention does not substantially improve weapon detection performance. Despite this null effect, the current study provides additional evidence regarding the impact of visual clutter on complex search performance by demonstrating significant reductions in weapon detection accuracy and search efficiency due to increasing levels of visual clutter. Further research should explore methods for improving complex visual search by considering the negative impacts of visual clutter and ensuring that both attention guidance and object recognition processes are facilitated during search.
Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/53034 |
Date | 12 January 2015 |
Creators | Darling, Cale M. |
Contributors | Durso, Francis T. |
Publisher | Georgia Institute of Technology |
Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
Language | en_US |
Detected Language | English |
Type | Thesis |
Format | application/pdf |
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