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Visual Search Models for Multiple Targets and Optimal Stopping Time  

Hong, Seung-Kweon (Dept. of ndustrial Engineering, State University of New York)
Park, Seikwon (Dept. of Industrial Engineering, Korea Air Force Academy)
Ryu, Seung Wan (Dept. of ndustrial Engineering, State University of New York)
Publication Information
Journal of Korean Institute of Industrial Engineers / v.29, no.2, 2003 , pp. 165-171 More about this Journal
Abstract
Visual search in an unstructured search field is a fruitful research area for computational modeling. Search models that describe relationship between search time and probability of target detection have been used for prediction of human search performance and provision of ideal goals for search training. Until recently, however, most of models were focused on detecting a single target in a search field, although, in practice, a search field includes multiple targets and search models for multiple targets may differ from search models for a single target. This study proposed a random search model for multiple targets, generalizing a random search model for a single target which is the most typical search model. To test this model, human search data were collected and compared with the model. This model well predicted human performance in visual search for multiple targets. This paper also proposed how to determine optimal stopping time in multiple-target search.
Keywords
multiple targets; visual search; human performance; optimal stopping time;
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