Doctor of Philosophy, The Ohio State University, 2016, Computer Science and Engineering

Scientists visualize their data and interact with them on computers in order to thoroughly understand them. Nowadays, data become so large and complex that it is impossible to display the entire data on a single image. Scientific visualization often suffers from visual clutter problem because of high spacial resolution/dimension and temporal resolution. Interacting with the visualizations of large data, on the other hand, allows users to dynamically explore different parts of the data and gradually understand all information in the data. Information congestion and visual clutter exist in visualizations of different kinds of data, such as flow field data, tensor field data, and time-varying data. Occlusion presents a major challenge in visualizing 3D flow and tensor fields using streamlines. Displaying too many streamlines creates a dense visualization filled with occluded structures, but displaying too few streams risks losing important features. Glyph as a powerful multivariate visualization technique is used to visualize data through its visual channels. Placing large number of glyphs over the entire 3D space results in occlusion and visual clutter that make the visualization ineffective. To avoid the occlusion in streamline and glyph visualization, we propose a view-dependent interactive 3D lens that removes the occluding streamlines/glyphs by pulling the them aside through animations. High resolution simulations are capable of generating very large vector fields that are expensive to store and analyze. In addition, the noise and/or uncertainty contained in the data often affects the quality of visualization by producing visual clutter that interferes with both the interpretation and identification of important features. Instead, we can store the distributions of many vector orientations and visualize the distributions with 3D glyphs, which largely reduce visual clutter. Empowered by rapid advance of high performance computer architectures and software, it is (open full item for complete abstract)

Committee: Han-Wei Shen (Advisor); Huamin Wang (Committee Member); Arnab Nandi (Committee Member) Subjects: Computer Engineering; Computer Science