Degree Type
Dissertation
Date of Award
2016
Degree Name
Doctor of Philosophy
Department
Theses & dissertations (Interdisciplinary)
Major
Human Computer Interaction
First Advisor
James Oliver
Second Advisor
Joseph Zambreno
Abstract
The ever-increasingly complex designs emanating from various companies are leading to a data explosion that is far outstripping the growth in computing processing power. The traditional large model visualization approaches used for rendering these data sets are quickly becoming insufficient, thus leading to a greater adoption of the new massive model visualization approaches designed to handle these arbitrarily sized data sets. Most new approaches utilize GPU occlusion queries that limit the data needed for loading and rendering to only those which can potentially contribute to the final image. By doing so, these approaches introduce disocclusion artifacts that often reduce the quality of the resulting visualization as a camera is maneuvered through the scene. The present research will demonstrate that shader based depth reprojection and OpenGL atomic writes not only increase the performance of an existing system based upon OpenGL occlusion queries, but also reduce the amount of perceived disocclusion artifacts.
DOI
https://doi.org/10.31274/etd-180810-5291
Copyright Owner
Jeremy S. Bennett
Copyright Date
2016
Language
en
File Format
application/pdf
File Size
87 pages
Recommended Citation
Bennett, Jeremy S., "Massive Model Visualization: A Practical Solution" (2016). Graduate Theses and Dissertations. 15663.
https://lib.dr.iastate.edu/etd/15663