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dc.contributor.advisorBorges, Carlos F.
dc.contributor.authorStarling, James Kendall.
dc.date.accessioned2012-03-14T17:46:08Z
dc.date.available2012-03-14T17:46:08Z
dc.date.issued2011-06
dc.identifier.urihttp://hdl.handle.net/10945/5622
dc.descriptionApproved for public release; distribution is unlimited.en_US
dc.description.abstractSearch and Target Acquisition (STA) in military simulations is the process of first identifying targets in a particular setting, then determining the probability of detection. This study will focus on the search aspect in STA, particularly with unaided vision. Current algorithms in combat models use an antiquated windshield wiper search pattern when conducting search. The studies used to determine these patterns used aided vision, such as binoculars or night vision devices. Very little research has been conducted for unaided vision and particularly not in urban environments. This study will use a data set taken from an earlier study in Fort Benning, GA, which captured the fixation points of 27 participants in simulated urban environments. This study achieved strong results showing that search is driven by salient scene information and is not random, using a series of nonparametric tests. The proposed algorithm, using points of interest (POIs) for the salient scene information, showed promising results for predicting the initial direction of search from the empirical data. However, the best results were realized when breaking the field of regard (FOR) into a small number of fields of view (FOVs).en_US
dc.description.urihttp://archive.org/details/prioritizingunai109455622
dc.format.extentxiv, 67 p. : some col. ill.en_US
dc.publisherMonterey, California. Naval Postgraduate Schoolen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. As such, it is in the public domain, and under the provisions of Title 17, United States Code, Section 105, may not be copyrighted.en_US
dc.subject.lcshNight vision devicesen_US
dc.titlePrioritizing unaided human search in military simulationsen_US
dc.typeThesisen_US
dc.contributor.secondreaderEvangelista, Paul F.
dc.contributor.corporateNaval Postgraduate School (U.S.)
dc.contributor.departmentApplied Mathematics
dc.identifier.oclc743341045
etd.thesisdegree.nameM.S.en_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.disciplineApplied Mathematicsen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US
etd.verifiednoen_US


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