Profile

Andrea Schnorr, M. Sc.


Publications


Tom Vierjahn, Andrea Schnorr, Benjamin Weyers, Dominik Denker , Ingo Wald, Christoph Garth, Torsten Wolfgang Kuhlen, Bernd Hentschel
Eurographics Symposium on Parallel Graphics and Visualization (2017)

Dissipation elements (DE) define a geometrical structure for the analysis of small-scale turbulence. Existing analyses based on DEs focus on a statistical treatment of large populations of DEs. In this paper, we propose a method for the interactive visualization of the geometrical shape of DE populations. We follow a two-step approach: in a pre-processing step, we approximate individual DEs by tube-like, implicit shapes with elliptical cross sections of varying radii; we then render these approximations by direct ray-casting thereby avoiding the need for costly generation of detailed, explicit geometry for rasterization. Our results demonstrate that the approximation gives a reasonable representation of DE geometries and the rendering performance is suitable for interactive use.

» Show BibTeX

@InProceedings{Vierjahn2017,
booktitle = {Eurographics Symposium on Parallel Graphics and Visualization},
author = {Tom Vierjahn and Andrea Schnorr and Benjamin Weyers and Dominik Denker and Ingo Wald and Christoph Garth and Torsten W. Kuhlen and Bernd Hentschel},
title = {Interactive Exploration of Dissipation Element Geometry},
year = {2017},
pages = {53--62},
ISSN = {1727-348X},
ISBN = {978-3-03868-034-5},
doi = {10.2312/pgv.20171093},
}






Andrea Schnorr, Sebastian Freitag, Dirk Helmrich, Torsten Wolfgang Kuhlen, Bernd Hentschel
LDAV 2016 – The 6th IEEE Symposium on Large Data Analysis and Visualization

We present an approach for tracking space-filling features based on a two-step algorithm utilizing two graph optimization techniques. First, one-to-one assignments between successive time steps are found by a matching on a weighted, bi-partite graph. Second, events are detected by computing an independent set on potential event explanations. The main objective of this work is investigating options for formal evaluation of complex feature tracking algorithms in the absence of ground truth data.

» Show BibTeX

@INPROCEEDINGS{Schnorr2016, author = {Andrea Schnorr and Sebastian Freitag and Dirk Helmrich and Torsten W. Kuhlen and Bernd Hentschel}, title = {{F}ormal {E}valuation {S}trategies for {F}eature {T}racking}, booktitle = Proc # { the } # LDAV, year = {2016}, pages = {103--104}, abstract = { We present an approach for tracking space-filling features based on a two-step algorithm utilizing two graph optimization techniques. First, one-to-one assignments between successive time steps are found by a matching on a weighted, bi-partite graph. Second, events are detected by computing an independent set on potential event explanations. The main objective of this work is investigating options for formal evaluation of complex feature tracking algorithms in the absence of ground truth data.
}, doi = { 10.1109/LDAV.2016.7874339}}






Andrea Schnorr, Sebastian Freitag, Torsten Wolfgang Kuhlen, Bernd Hentschel
EG/VGTC Conference on Visualization, EuroVis 2016

We present a novel approach for tracking space-filling features, i.e., a set of features covering the entire domain. The assignment between successive time steps is determined by a two-step, global optimization scheme. First, a maximum-weight, maximal matching on a bi-partite graph is computed to provide one-to-one assignments between features of successive time steps. Second, events are detected in a subsequent step; here the matching step serves to restrict the exponentially large set of potential solutions. To this end, we compute an independent set on a graph representing conflicting event explanations. The method is evaluated by tracking dissipation elements, a structure definition from turbulent flow analysis.

Honorable Mention Award!

» Show BibTeX

@inproceedings {eurp.20161146,
booktitle = {EuroVis 2016 - Posters},
editor = {Tobias Isenberg and Filip Sadlo},
title = {{Tracking Space-Filling Features by Two-Step Optimization}},
author = {Schnorr, Andrea and Freitag, Sebastian and Kuhlen, Torsten W. and Hentschel, Bernd},
year = {2016},
publisher = {The Eurographics Association},
pages = {77--79},
ISBN = {978-3-03868-015-4},
DOI = {10.2312/eurp.20161146}
}






Bernd Hentschel, Jens Henrik Göbbert, Michael Klemm, Paul Springer, Andrea Schnorr, Torsten Wolfgang Kuhlen
Eurographics Symposium on Parallel Graphics and Visualization (2015)

The advection of integral lines is an important computational kernel in vector field visualization. We investigate how this kernel can profit from vector (SIMD) extensions in modern CPUs. As a baseline, we formulate a streamline tracing algorithm that facilitates auto-vectorization by an optimizing compiler. We analyze this algorithm and propose two different optimizations. Our results show that particle tracing does not per se benefit from SIMD computation. Based on a careful analysis of the auto-vectorized code, we propose an optimized data access routine and a re-packing scheme which increases average SIMD efficiency. We evaluate our approach on three different, turbulent flow fields. Our optimized approaches increase integration performance up to 5:6 over our baseline measurement. We conclude with a discussion of current limitations and aspects for future work.

» Show BibTeX

@INPROCEEDINGS{Hentschel2015,
author = {Bernd Hentschel and Jens Henrik G{\"o}bbert and Michael Klemm and
Paul Springer and Andrea Schnorr and Torsten W. Kuhlen},
title = {{P}acket-{O}riented {S}treamline {T}racing on {M}odern {SIMD}
{A}rchitectures},
booktitle = {Proceedings of the Eurographics Symposium on Parallel Graphics
and Visualization},
year = {2015},
pages = {43--52},
abstract = {The advection of integral lines is an important computational
kernel in vector field visualization. We investigate
how this kernel can profit from vector (SIMD) extensions in modern CPUs. As a
baseline, we formulate a streamline
tracing algorithm that facilitates auto-vectorization by an optimizing compiler.
We analyze this algorithm and
propose two different optimizations. Our results show that particle tracing does
not per se benefit from SIMD computation.
Based on a careful analysis of the auto-vectorized code, we propose an optimized
data access routine
and a re-packing scheme which increases average SIMD efficiency. We evaluate our
approach on three different,
turbulent flow fields. Our optimized approaches increase integration performance
up to 5.6x over our baseline
measurement. We conclude with a discussion of current limitations and aspects
for future work.}
}






Andrea Schnorr, Jens Henrik Göbbert, Torsten Wolfgang Kuhlen, Bernd Hentschel
Large Data Analysis and Visualization (LDAV), 2015

We present a novel approach for tracking space-filling features, i.e. a set of features which covers the entire domain. In contrast to previous work, we determine the assignment between features from successive time steps by computing a globally optimal, maximum-weight, maximal matching on a weighted, bi-partite graph. We demonstrate the method's functionality by tracking dissipation elements (DEs), a space-filling structure definition from turbulent flow analysis. The ability to track DEs over time enables researchers from fluid mechanics to extend their analysis beyond the assessment of static flow fields to time-dependent settings.

» Show BibTeX

@INPROCEEDINGS{Schnorr2015,
author = {Andrea Schnorr and Jens-Henrik Goebbert and Torsten W. Kuhlen and Bernd Hentschel},
title = {{T}racking {S}pace-{F}illing {S}tructures in {T}urbulent {F}lows},
booktitle = Proc # { the } # LDAV,
year = {2015},
pages = {143--144},
abstract = {We present a novel approach for tracking space-filling features, i.e. a set of features which covers the entire domain. In contrast to previous work, we determine the assignment between features from successive time steps by computing a globally optimal, maximum-weight, maximal matching on a weighted, bi-partite graph. We demonstrate the method's functionality by tracking dissipation elements (DEs), a space-filling structure definition from turbulent flow analysis. The abilitytotrack DEs over time enables researchers from fluid mechanics to extend their analysis beyond the assessment of static flow fields to time-dependent settings.},
doi = {10.1109/LDAV.2015.7348089},
keywords = {Feature Tracking, Weighted, Bi-Partite Matching, Flow
Visualization, Dissipation Elements}
}





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