Information
- Publication Type: Master Thesis
- Workgroup(s)/Project(s):
- Date: July 2020
- Date (Start): 21. February 2010
- Date (End): 27. July 2020
- Diploma Examination: 27. July 2020
- Open Access: yes
- First Supervisor: Stefan Bruckner
- Pages: 110
- Keywords: Molecular Visualization, Real-Time Rendering, Computer Graphics
Abstract
The complexity of biomolecular data sets is both high, and still rising. Three-dimensional models of molecules are used in research to test and investigate their properties. Such models can consist of several millions of atoms. Additionally, visual enhancement methods
and molecular surface models are helpful when visualizing molecules. There is therefore a demand for efficient and flexible data structures to accommodate such large point-based data sets.
Existing solutions in the field of molecular visualization for large data sets include the use of, in most cases, regular grid-based data structures, as well as levels of detail. Other papers focus on repeating structures or improving the efficiency of surface models.
We propose an octree-based data structure that divides space into areas of similar density, and provides several levels of detail. Our approach is optimized for a single time-step, moving much of the computational overhead into a pre-processing step. This allows us to speed up frame rates for interactive visualizations using visibility culling, least recently used caching based on the pre-built octree data structure, and level of detail solutions such as depth-based level of detail rendering.
In our evaluation, we show that level of detail rendering significantly improves frame rates, especially in the case of distance-based level of detail selection while keeping the amount of details in the foreground high. Both the possibility to reduce the resolution and the
caching strategy that allows us to only upload visible parts of the data set make it possible to render data sets that previously exhausted the capacities of our test set-up. We found the main advantage of a density based octree, instead of a regular division of space, to be
in neighbourhood-based calculations, such as the clustering algorithm required to build levels of detail. This could prove particularly useful for the implementation of a Solvent Excluded Surface (SES) representation model, which would be an important feature to include when developing the framework further.
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BibTeX
@mastersthesis{Nowak_2020,
title = "Hierarchical Multi-resolution Data Structure for Molecular
Visualization",
author = "Milena Nowak",
year = "2020",
abstract = "The complexity of biomolecular data sets is both high, and
still rising. Three-dimensional models of molecules are used
in research to test and investigate their properties. Such
models can consist of several millions of atoms.
Additionally, visual enhancement methods and molecular
surface models are helpful when visualizing molecules. There
is therefore a demand for efficient and flexible data
structures to accommodate such large point-based data sets.
Existing solutions in the field of molecular visualization
for large data sets include the use of, in most cases,
regular grid-based data structures, as well as levels of
detail. Other papers focus on repeating structures or
improving the efficiency of surface models. We propose an
octree-based data structure that divides space into areas of
similar density, and provides several levels of detail. Our
approach is optimized for a single time-step, moving much of
the computational overhead into a pre-processing step. This
allows us to speed up frame rates for interactive
visualizations using visibility culling, least recently used
caching based on the pre-built octree data structure, and
level of detail solutions such as depth-based level of
detail rendering. In our evaluation, we show that level of
detail rendering significantly improves frame rates,
especially in the case of distance-based level of detail
selection while keeping the amount of details in the
foreground high. Both the possibility to reduce the
resolution and the caching strategy that allows us to only
upload visible parts of the data set make it possible to
render data sets that previously exhausted the capacities of
our test set-up. We found the main advantage of a density
based octree, instead of a regular division of space, to be
in neighbourhood-based calculations, such as the clustering
algorithm required to build levels of detail. This could
prove particularly useful for the implementation of a
Solvent Excluded Surface (SES) representation model, which
would be an important feature to include when developing the
framework further.",
month = jul,
pages = "110",
address = "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria",
school = "Research Unit of Computer Graphics, Institute of Visual
Computing and Human-Centered Technology, Faculty of
Informatics, TU Wien",
keywords = "Molecular Visualization, Real-Time Rendering, Computer
Graphics",
URL = "https://www.cg.tuwien.ac.at/research/publications/2020/Nowak_2020/",
}
Master Thesis