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A T T E N T I O N: Please note that day and room differ from our
normal schedule.<br>
<br>
<br>
<br>
I N V I T A T I O N<br>
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<font face="sans-serif">===============================================<br>
<br>
to the Research Seminar 'Computer Graphics, Image Processing, and
Visualization'<br>
<br>
</font><font face="sans-serif"> on<font face="sans-serif">
Monday, May 30th, 2016, at 1:15 PM,<br>
in Room P-702 in the Paulinum, Augustusplatz.</font><br>
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<br>
<br>
<br>
We will be hearing a total of three talks.<br>
<br>
Two of them are given by<br>
<br>
Roxana Bujack<br>
Computer Graphics and HCI Group<br>
University of Kaiserslautern.<br>
<br>
The first talk is entitled<br>
<br>
"Analysis of Error in Interpolation-Based Pathline Tracing".<br>
<br>
Abstract:<br>
<br>
Chandler et al. presented interpolation-based pathline tracing
as an<br>
alternative method to numerical integration for advecting
tracers in<br>
particle-based flow fields. Through their experiments, they
showed that an<br>
interpolation-based method has lower error than a numerical<br>
integration-based method for particle tracing. In this paper we
seek to<br>
understand the sources of the error in interpolation-based
pathline<br>
tracing.<br>
We present a formal analysis of the theoretical bound on the
error when<br>
advecting pathlines using this method. Additionally, we
characterize the<br>
error in experimental data sets using characteristics of the
flow field<br>
such as neighborhood change, flow divergence, and length of the
reference<br>
pathline.<br>
Understanding the sources of error in an advection method is
important to<br>
know where there may be uncertainty in the resulting analysis.
We find that<br>
for interpolation-based pathline tracing the error is most
closely related<br>
to the divergence in the flow field.<br>
<br>
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The second talk is entitled<br>
<br>
"Strategic Initiatives for Flow Visualization in Environmental
Sciences".<br>
<br>
Abstract:<br>
<br>
Flow plays a big role in the environmental sciences, but there
are major<br>
differences between theoretically available and practically
applied<br>
visualization techniques.<br>
This paper surveys various techniques in computational and
environmental<br>
flow visualization, identifies challenges, and suggests
strategic<br>
initiatives on how to bridge the gap.<br>
<br>
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<br>
The third talk is given by<br>
<br>
Tom Liebmann<br>
Image and Signal Processing Group<br>
Leipzig University<br>
<br>
Abstract:<br>
<br>
Simulations and measurements often result in scalar fields with
uncertainty<br>
due to errors or output sensitivity estimates. Methods for
analyzing<br>
topological features of such fields usually are not capable of
handling all<br>
aspects of the data. They either are not deterministic due to
using Monte<br>
Carlo approaches, approximate the data with confidence
intervals, or miss<br>
out on incorporating important properties, such as correlation.
In this<br>
paper, we focus on the analysis of critical points of
Gaussian-distributed<br>
scalar fields. We introduce methods to deterministically extract
critical<br>
points, approximate their probability with high precision, and
even capture<br>
relations between them resulting in an abstract graph
representation.<br>
Unlike many other methods, we incorporate all information
contained in the<br>
data including global correlation. Our work therefore is a first
step<br>
towards a reliable and complete description of topological
features of<br>
Gaussian-distributed scalar fields.<br>
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<br>
<br>
On behalf of Professor Scheuermann all those interested are
cordially invited to attend.<br>
<br>
Yours sincerely,</font><br>
Tom Liebmann
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