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Position uncertainty, clutter, and performance in naturalistic search tasks
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Semizer, Yelda. Position uncertainty, clutter, and performance in naturalistic search tasks. Retrieved from https://doi.org/doi:10.7282/t3-sp54-m464

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TitlePosition uncertainty, clutter, and performance in naturalistic search tasks
NameSemizer, Yelda (author); Michel, Melchi M (chair); Rutgers University; School of Graduate Studies
Date Created2019
Other Date2019-05 (degree)
SubjectVisual search, Psychology, Searching behavior, Visual perception, Uncertainty
Extent1 online resource (x, 90 pages) : illustrations
DescriptionUncertainty regarding the position of target objects in natural scenes is a fundamental property of visual search tasks. As visual clutter in natural scenes increases, extrinsic position uncertainty (i.e., set size) also increases. While studies of visual search have repeatedly demonstrated that clutter impairs search performance in natural scenes, these studies have not attempted to disentangle the effects of search set size from those of clutter per se. Moreover, most of the clutter models used in these studies do not take the properties of the search targets into account. Thus, this dissertation has two main objectives: (1) to quantify the effect of clutter on search performance for categorical targets when the set size (i.e., extrinsic position uncertainty) is controlled and (2) to determine what visual features of categorical search targets and backgrounds are important in measuring clutter. In Study I, we investigate the effect of natural image clutter on performance in an overt search for categorical targets when the search set size is controlled. Observers completed a search task that required detecting and localizing common objects in a set of natural images. The images were sorted into high and low clutter conditions based on the clutter metric. The search set size was varied independently, by fixing the number and positions of potential targets across set size conditions within a block of trials. Within each fixed set size condition, search times increased as a function of increasing clutter, suggesting that clutter degrades overt search performance independently of set size. In Study II, we propose new clutter metrics based on two types of target-background similarity (i.e., exemplar level and category level) to predict the effect of clutter on search performance. In a nutshell, our metrics measured the similarity between target and background features (i.e., orientation subbands) in images while also accounting for size of a search target. Our results demonstrated that both the exemplar clutter metric and the category clutter metric predicted search performance. Overall, these two studies suggest that intrinsic position uncertainty and target-background similarity should be incorporated into models of visual search and clutter in determining performance in natural search tasks.
NotePh.D.
NoteIncludes bibliographical references
Genretheses, ETD doctoral
Persistent URLhttps://doi.org/doi:10.7282/t3-sp54-m464
LanguageEnglish
CollectionSchool of Graduate Studies Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
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