Attention and visual memory in visualization and computer graphics

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 efficiency and effectiveness. This paper surveys research on attention and visual perception, with a specific focus on results that have direct relevance to visualization and visual analytics. We discuss theories of low-level visual perception, then show how these findings 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

An intuitive model of perceptual grouping for HCI design

ABSTRACT Understanding and exploiting the abilities of the human visual system is an important part of the design of usable user interfaces and information visualizations. Good design enables quick, easy and veridical perception of key components of that design. An important facet of human vision is its ability to seemingly effortlessly perform "perceptual organization"; it transforms individual feature estimates into perception of coherent regions, structures, and objects. We perceive regions grouped by proximity and feature similarity, grouping of curves by good continuation, and grouping of regions of coherent texture. In this paper, we discuss a simple model for a broad range of perceptual grouping phenomena. It takes as input an arbitrary image, and returns a structure describing the predicted visual organization of the image. We demonstrate that this model can capture aspects of traditional design rules, and predicts visual percepts in classic perceptual grouping displays

Modern process visualization techniques in process data management systems

Tremendous advancements in sensors, communication networks, mobile devices and cloud-based technologies along with their decreasing prices have enabled the Industrial Internet of Things. The two major consequences observed are the exponential growth of collected process data in industrial processes and the need for visualizing it on mobile devices. These have created a demand for new, more efficient and more powerful techniques to gain value from the larger data sets that work seamlessly across multiple platforms. One such technique is visualizing process data in three dimensional space which is implemented in this Master’s thesis. 3D visualization was demonstrated to offer immense opportunities to industries by enhancing data interactivity and enabling the partitioning of process data into multiple layers. The biggest challenge in the implementation of this technique was obtaining 3D models of the manufacturing equipment, thus indicating the need to create and provide 3D models as a part of the package