title: Mapping the color space of saccadic selectivity in visual search.
abstract: Color coding is used to guide attention in computer displays for such critical tasks as baggage screening or air traffic control. It has been shown that a display object attracts more attention if its color is more similar to the color for which one is searching. However, what does similar precisely mean? Can we predict the amount of attention that a display color will receive during a search for a given target color? To tackle this question, two color-search experiments measuring the selectivity of saccadic eye movements and mapping out its underlying color space were conducted. A variety of mathematical models, predicting saccadic selectivity for given target and display colors, were devised and evaluated. The results suggest that applying a Gaussian function to a weighted Euclidean distance in a slightly modified HSI color space is the best predictor of saccadic selectivity in the chosen paradigm. Hue and intensity information by itself provides a basis for useful predictors, spanning a possibly spherical color space of saccadic selectivity. Although the current models cannot predict saccadic selectivity values for a wide variety of visual search tasks, they reveal some characteristics of color search that are of both theoretical and applied interest, such as for the design of human-computer interfaces.
authors.affiliation: Department of Computer Science, University of Massachusetts at Boston.
authors.forename: Yun
authors.initials: Y
authors.lastname: Xu
authors.forename: Emily C
authors.initials: EC
authors.lastname: Higgins
authors.forename: Mei
authors.initials: M
authors.lastname: Xiao
authors.forename: Marc
authors.initials: M
authors.lastname: Pomplun