Abstract

Three-dimensional vector fields are common datasets throughout the sciences. They often represent physical phenomena which are largely invisible to us in the real world, like wind patterns and ocean currents. Computer-aided visualization is a powerful tool which can represent data in any way we choose through digital graphics. Visualizing 3D vector fields is inherently difficult due to issues such as visual clutter, self-occlusion, and the difficulty of providing depth cues that adequately support the perception of flow direction in 3D space. Cutting planes are often used to overcome these issues by presenting slices of data which are more cognitively manageable. The existing literature provides many techniques for visualizing the flow through these cutting planes; however, there is a lack of empirical studies focused on the underlying perceptual cues that make popular techniques successful. The most valuable depth cue for the perception of other kinds of 3D data, notably 3D networks and 3D point clouds, is structure-from-motion (also called the Kinetic Depth Effect); another powerful depth cue is stereoscopic viewing, but none of these cues have been fully examined in the context of flow visualization. This dissertation presents a series of quantitative human factors studies which evaluate depth and direction cues in the context of cutting plane glyph designs for exploring and analyzing 3D flow fields. The results of the studies are distilled into a set of design guidelines to improve the effectiveness of 3D flow field visualizations, and those guidelines are implemented as an immersive, interactive 3D flow visualization proof-of-concept application.

Presenter Bio

Drew Stevens hails from the beautiful city of Vallejo, California in the San Francisco Bay Area. After earning his bachelor's degree in music composition from UC Davis, he relocated to Los Angeles where he worked as a programmer and web developer in the music industry for a number of years while enjoying the big city life and making up jingles during his hours-long daily commute. He eventually moved away from Southern California to the Sacramento area to pursue his educational ambitions in the natural sciences and mathematics, after which he began work as a scientist at Iris Environmental, a small environmental consulting company in Oakland. At Iris, Drew managed large environmental datasets, providing analysis and visualization products to clients as well as authoring technical reports. He also has experience collecting environmental data in the field to support projects spanning one-off to multi-week sampling programs. His work visualizing subsurface conditions and contamination lead him to the CCOM Data Visualization Research Lab, where he has pursued a doctorate in computer science.

Publication Date

2-11-2021

Document Type

Presentation

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