Harnessing Preattentive Processes for Multivariate Data Visualization

A new method for designing multivariate data visualization tools is presented. These tools allow users to perform simple tasks such as estimation, target detection, and detection of data boundaries rapidly and accurately. Our design technique is based on principles arising from an area of cognitive psychology called preattentive processing. Preattentive processing involves visual features that can be detected by the human visual system without focusing attention on particular regions in an image. Examples of preattentive features include colour, orientation, intensity, size, shape, curvature, and line length. Detection is performed very rapidly by the visual system, almost certainly using a large degree of parallelism. We studied two known preattentive features, hue and orientation. The particular question investigated is whether rapid and accurate estimation is possible using these preattentive features. Experiments that simulated displays using our preattentive visualization tool were run. Analysis of the results of the experiments showed that rapid and accurate estimation is possible with both hue and orientation. A second question, whether interaction occurs between the two features, was answered negatively. This suggests that these and perhaps other preattentive features can be used to create visualization tools which allow high-speed multivariate data analysis.