Abstract-A fundamental goal of visualization is to produce images of data that support visual analysis, exploration, and discovery of novel insights. An important consideration during visualization design is the role of human visual perception. How we "see" details in an image can directly impact a viewer's ef ciency and effectiveness. This article surveys research on attention and visual perception, with a speci c focus on results that have direct relevance to visualization and visual analytics. We discuss theories of low-level visual perception, then show how these ndings form a foundation for more recent work on visual memory and visual attention. We conclude with a brief overview of how knowledge of visual attention and visual memory is being applied in visualization and graphics. We also discuss how challenges in visualization are motivating research in psychophysics.

This paper presents a new method for using texture and color to visualize multivariate data elements arranged on an underlying height field. We combine simple texture patterns with perceptually uniform colors to increase the number of attribute values we can display simultaneously. Our technique builds multicolored perceptual texture elements (or pexels) to represent each data element. Attribute values encoded in an element are used to vary the appearance of its pexel. Texture and color patterns that form when the pexels are displayed can be used to rapidly and accurately explore the dataset. Our pexels are built by varying three separate texture dimensions: height, density, and regularity. Results from computer graphics, computer vision, and human visual psychophysics have identified these dimensions as important for the formation of perceptual texture patterns. The pexels are colored using a selection technique that controls color distance, linear separation, and color category. Proper use of these criteria guarantees colors that are equally distinguishable from one another. We describe a set of controlled experiments that demonstrate the effectiveness of our texture dimensions and color selection criteria. We then discuss new work that studies how texture and color can be used simultaneously in a single display. Our results show that variations of height and density have no effect on color segmentation, but that random color patterns can interfere with texture segmentation. As the difficulty of the visual detection task increases, so too does the amount of color on texture interference increase. We conclude by demonstrating the applicability of our approach to a real-world problem, the tracking of typhoon conditions in Southeast Asia.

A new method is presented for performing rapid and accurate numerical estimation. The method is derived from an area of human cognitive psychology called preattentive processing. Preattentive processing refers to an initial organization of the visual field based on cognitive operations believed to be rapid, automatic, and spatially parallel. Examples of visual features that can be detected in this way include hue, intensity, orientation, size, and motion. We believe that studies from preattentive vision should be used to assist in the design of visualization tools, especially those for which high-speed target detection, boundary identification, and region detection are important. In our present study, we investigated two known preattentive features (hue and orientation) in the context of a new task (numerical estimation) in order to see whether preattentive estimation was possible. Our experiments tested displays that were designed to visualize data from salmon migration simulations. The results showed that rapid and accurate estimation was indeed possible using either hue or orientation. Furthermore, random variation in one of these features resulted in no interference when subjects estimated the percentage of the other. To test the generality of our results, we varied two important display parameters-display duration and feature difference-and found boundary conditions for each. Implications of our results for application to real-world data and tasks are discussed.

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The findings from this study suggest generalist nurses are the frontline providers of care for mental health consumers in rural EDs and UCCs. Nurses feel ill-equipped for assessing and managing mental health presentations, relying heavily on local mental health teams and telephone triage who provide limited onsite support. The need to support nurses through training and mentoring relationships with community mental health teams is highlighted by this study in conjunction with improving the delivery of mental health services in rural areas.