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

Language

en

File Format

application/pdf

File Size

87 pages

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