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Camouflage assessment: Machine and human

Research output: Contribution to journalArticle

Original languageEnglish
Pages (from-to)173-182
Number of pages10
JournalComputers in Industry
Volume99
Early online date3 Apr 2018
DOIs
DateAccepted/In press - 15 Mar 2018
DateE-pub ahead of print - 3 Apr 2018
DatePublished (current) - 1 Aug 2018

Abstract

A vision model is designed using low-level vision principles so that it can perform as a human observer model for camouflage assessment. In a camouflaged-object assessment task, using military patterns in an outdoor environment, human performance at detection and recognition is compared with the human observer model. This involved field data acquisition and subsequent image calibration, a human experiment, and the design of the vision model. Human and machine performance, at recognition and detection, of military patterns in two environments was found to correlate highly. Our model offers an inexpensive, automated, and objective method for the assessment of camouflage where it is impractical, or too expensive, to use human observers to evaluate the conspicuity of a large number of candidate patterns. Furthermore, the method should generalize to the assessment of visual conspicuity in non-military contexts.

    Research areas

  • Camouflage Assessment, Observer Modelling, Visual Search

Documents

Documents

  • Full-text PDF (accepted author manuscript)

    Rights statement: This is the author accepted manuscript (AAM). The final published version (version of record) is available online via Elsevier at https://www.sciencedirect.com/science/article/pii/S0166361517305705 . Please refer to any applicable terms of use of the publisher.

    Accepted author manuscript, 11 MB, PDF-document

    Embargo ends: 3/04/20

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    Licence: CC BY-NC-ND

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