Date of Award
Winter 2025
Project Type
Dissertation
Program or Major
Computer Science
Degree Name
Doctor of Philosophy
First Advisor
Thomas Butkiewicz
Second Advisor
Jenn Dijkstra
Third Advisor
Colin Ware
Abstract
This dissertation presents Focal Engine, a novel 3D visualization engine designed to bridge the gap between game engines and scientific visualization tools. Game engines offer accessible interfaces and high-performance rendering but struggle with large-scale scientific datasets, while tools like ParaView and VTK handle complex data structures effectively but lack intuitive editing capabilities and modern rendering features. Focal Engine combines the accessibility and rendering performance of game engines with the data handling capabilities and analytical tools of scientific visualization platforms. The engine's capabilities are validated through multiple applications and projects, for example: HabiCAT 3D performs 3D complexity measurements on ocean floor models with up to 300 million triangles as well as scans in point cloud format; a VR Point Cloud Editor handles datasets of several hundred million points at 90+ fps, meeting VR performance requirements that no existing commercial off-the-shelf engine can achieve. These and other applications demonstrate that Focal Engine enables analyses and visualizations previously infeasible with existing software, establishing it as a valuable addition to the toolbox of the scientific visualization community.
Recommended Citation
Beregovyi, Kindrat, "Focal Engine: Filling a Gap Between Game Engines and Big-Data Scientific Visualization Packages" (2025). Doctoral Dissertations. 2961.
https://scholars.unh.edu/dissertation/2961