Applying computational models of visual search to map design

Joshua M Shive, Purdue University


A regression model of visual search was developed and used to assign colors to items on maps to minimize search time. Data were collected from a visual search experiment and used to create a quantitative model of visual search that mimics human search of map displays. The parameterized model was used in a number of optimization tasks. Map display designs made by this simulation were tested experimentally. Follow-up experiments explored the effectiveness of the model’s feature representations and examined the model’s flexibility to assign colors in novel search situations. The model fits human performance, performs well on the optimization tasks, and can use the same set of model parameters to choose colors for items on maps with novel stimuli to predict performance. The benefits and limitations of using this approach to choose colors for items on maps are discussed.^




Gregory Francis, Purdue University.

Subject Area

Psychology, Cognitive

Off-Campus Purdue Users:
To access this dissertation, please log in to our
proxy server