Stefan Bruckner is a full professor in Visualization at the Department of Informatics of the University of Bergen, Norway. He received his master's degree (2004) and Ph.D. (2008), both in Computer Science, from the TU Wien, Austria, and was awarded the habilitation (venia docendi) in Practical Computer Science in 2012. Before his appointment in Bergen in 2013, he was an assistant professor at the Institute of Computer Graphics and Algorithms of the TU Wien.
His research interests include all aspects of data visualization, with a particular focus on interactive techniques for the exploration and analysis of spatial data. He has made significant contributions to areas such as illustrative visualization, volume rendering, smart visual interfaces, biomedical data visualization, and visual parameter space exploration. In addition to his contributions in basic research, he has successfully led industry collaborations with major companies such as GE Healthcare and Agfa HealthCare, and has 6 granted patents.
He is a recipient of the Eurographics Young Researcher Award, the Karl-Heinz-Höhne Award for Medical Visualization, and his research has received 8 best paper awards and honorable mentions at international events. He was program co-chair of EuroVis, PacificVis, the Eurographics Workshop on Visual Computing for Biology and Medicine, the Eurographics Medical Prize, and serves on the editorial board of Computers & Graphics. He is an ACM Distinguished Speaker, and a member of ACM SIGGRAPH, Eurographics, and the IEEE Computer Society.
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Publications
2018
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[Bibtex] @article {Stoppel-2018-FVI,
author = "Sergej Stoppel and Magnus Paulson Erga and Stefan Bruckner",
title = "Firefly: Virtual Illumination Drones for Interactive Visualization",
journal = "IEEE Transactions on Visualization and Computer Graphics (to appear)",
year = "2018",
abstract = "Light specification in three dimensional scenes is a complex problem and several approaches have been presented that aim to automate this process. However, there are many scenarios where a static light setup is insufficient, as the scene content and camera position may change. Simultaneous manual control over the camera and light position imposes a high cognitive load on the user. To address this challenge, we introduce a novel approach for automatic scene illumination with Fireflies. Fireflies are intelligent virtual light drones that illuminate the scene by traveling on a closed path. The Firefly path automatically adapts to changes in the scene based on an outcome-oriented energy function. To achieve interactive performance, we employ a parallel rendering pipeline for the light path evaluations. We provide a catalog of energy functions for various application scenarios and discuss the applicability of our method on several examples.",
pdf = "pdfs/VIS2018-Firefly.pdf",
vid = "vids/FinalVideo.mp4",
doi = "10.1109/TVCG.2018.2864656",
images = "images/Teaser.png",
thumbnails = "images/HeadRightCroppedThumbnail.png"
}![[YT]](http://vis.uib.no/wp-content/papercite-data/images/youtube.png)
[Bibtex] @INPROCEEDINGS {Stoppel-2018-SSW,
author = "Sergej Stoppel and Stefan Bruckner",
title = "Smart Surrogate Widgets for Direct Volume Manipulation",
booktitle = "Proceedings of IEEE PacificVis 2018",
year = "2018",
pages = "36--45",
month = "apr",
abstract = "Interaction is an essential aspect in volume visualization, yet common
manipulation tools such as bounding boxes or clipping plane
widgets provide rather crude tools as they neglect the complex structure
of the underlying data. In this paper, we introduce a novel
volume interaction approach based on smart widgets that are automatically
placed directly into the data in a visibility-driven manner.
By adapting to what the user actually sees, they act as proxies that
allow for goal-oriented modifications while still providing an intuitive
set of simple operations that is easy to control. In particular, our
method is well-suited for direct manipulation scenarios such as touch
screens, where traditional user interface elements commonly exhibit
limited utility. To evaluate out approach we conducted a qualitative
user study with nine participants with various backgrounds.",
pdf = "pdfs/Stoppel-2018-SSW.pdf",
images = "images/Stoppel-2018-SSW.jpg",
thumbnails = "images/Stoppel-2018-SSW.png",
youtube = "https://www.youtube.com/watch?v=wMRw-W0SrLk",
event = "IEEE PacificVis 2018",
keywords = "smart interfaces, volume manipulation, volume visualization",
doi = "10.1109/PacificVis.2018.00014"
}@ARTICLE {Bruckner-2018-MSD,
author = "Stefan Bruckner and Tobias Isenberg and Timo Ropinski and Alexander Wiebel",
title = "A Model of Spatial Directness in Interactive Visualization",
journal = "IEEE Transactions on Visualization and Computer Graphics (accepted for publication, to appear in an upcoming issue)",
year = "2018",
abstract = "We discuss the concept of directness in the context of spatial interaction with visualization. In particular, we propose a model
that allows practitioners to analyze and describe the spatial directness of interaction techniques, ultimately to be able to better understand
interaction issues that may affect usability. To reach these goals, we distinguish between different types of directness. Each type of
directness depends on a particular mapping between different spaces, for which we consider the data space, the visualization space, the
output space, the user space, the manipulation space, and the interaction space. In addition to the introduction of the model itself, we also
show how to apply it to several real-world interaction scenarios in visualization, and thus discuss the resulting types of spatial directness,
without recommending either more direct or more indirect interaction techniques. In particular, we will demonstrate descriptive and
evaluative usage of the proposed model, and also briefly discuss its generative usage.",
pdf = "pdfs/Bruckner-2018-MSD.pdf",
images = "images/Bruckner-2018-MSD.jpg",
thumbnails = "images/Bruckner-2018-MSD.png"
}@ARTICLE {Magnus-2018-VPI,
author = "Jens G. Magnus and Stefan Bruckner",
title = "Interactive Dynamic Volume Illumination with Refraction and Caustics",
journal = "IEEE Transactions on Visualization and Computer Graphics",
year = "2018",
volume = "24",
number = "1",
pages = "984--993",
month = "jan",
abstract = "In recent years, significant progress has been made in
developing high-quality interactive methods for realistic volume
illumination. However, refraction -- despite being an important aspect
of light propagation in participating media -- has so far only received
little attention. In this paper, we present a novel approach for
refractive volume illumination including caustics capable of interactive
frame rates. By interleaving light and viewing ray propagation, our
technique avoids memory-intensive storage of illumination information
and does not require any precomputation. It is fully dynamic and all
parameters such as light position and transfer function can be modified
interactively without a performance penalty.",
pdf = "pdfs/Magnus-2018-IDV.pdf",
images = "images/Magnus-2018-IDV.jpg",
thumbnails = "images/Magnus-2018-IDV.png",
youtube = "https://www.youtube.com/watch?v=3tn6sSXw4NQ",
doi = "10.1109/TVCG.2017.2744438",
event = "IEEE SciVis 2017",
keywords = "interactive volume rendering, illumination, refraction, shadows, caustics",
location = "Phoenix, USA"
}2017
[Bibtex] @ARTICLE {Mindek-2017-DVN,
author = "Peter Mindek and Gabriel Mistelbauer and Meister Eduard Gr{\"o}ller and Stefan Bruckner",
title = "Data-Sensitive Visual Navigation",
journal = "Computers \& Graphics",
year = "2017",
volume = "67",
pages = "77--85",
month = "oct",
abstract = "In visualization systems it is often the case that the
changes of the input parameters are not proportional to the visual
change of the generated output. In this paper, we propose a model for
enabling data-sensitive navigation for user-interface elements. This
model is applied to normalize the user input according to the visual
change, and also to visually communicate this normalization. In this
way, the exploration of heterogeneous data using common interaction
elements can be performed in an efficient way. We apply our model to the
field of medical visualization and present guided navigation tools for
traversing vascular structures and for camera rotation around 3D
volumes. The presented examples demonstrate that the model scales to
user-interface elements where multiple parameters are set
simultaneously.",
pdf = "pdfs/Mindek-2017-DVN.pdf",
images = "images/Mindek-2017-DVN.jpg",
thumbnails = "images/Mindek-2017-DVN.png",
youtube = "https://www.youtube.com/watch?v=FnhbjX7BRXI",
note = "SCCG 2017 Best Paper Award",
doi = "10.1016/j.cag.2017.05.012",
event = "SCCG 2017",
keywords = "navigation, exploration, medical visualization",
location = "Mikulov, Czech Republic"
}@ARTICLE {Diehl-2017-AVA,
author = "Alexandra Diehl and Leandro Pelorosso and Kresimir Matkovic and Juan Ruiz and Meister Eduard Gr{\"o}ller and Stefan Bruckner",
title = "Albero: A Visual Analytics Approach for Probabilistic Weather Forecasting",
journal = "Computer Graphics Forum",
year = "2017",
volume = "36",
number = "7",
pages = "135--144",
month = "oct",
abstract = "Probabilistic weather forecasts are amongst the most popular
ways to quantify numerical forecast uncertainties. The analog
regression method can quantify uncertainties and express them as
probabilities. The method comprises the analysis of errors
from a large database of past forecasts generated with a specific
numerical model and observational data. Current visualization
tools based on this method are essentially automated and provide limited
analysis capabilities. In this paper, we propose a novel
approach that breaks down the automatic process using the experience and
knowledge of the users and creates a new interactive
visual workflow. Our approach allows forecasters to study probabilistic
forecasts, their inner analogs and observations, their
associated spatial errors, and additional statistical information by
means of coordinated and linked views. We designed the
presented solution following a participatory methodology together with
domain experts. Several meteorologists with different
backgrounds validated the approach. Two case studies illustrate the
capabilities of our solution. It successfully facilitates the
analysis of uncertainty and systematic model biases for improved
decision-making and process-quality measurements.",
pdf = "pdfs/Diehl-2017-AVA.pdf",
images = "images/Diehl-2017-AVA.jpg",
thumbnails = "images/Diehl-2017-AVA.png",
youtube = "https://www.youtube.com/watch?v=-yqoeEgkz28",
doi = "10.1111/cgf.13279",
keywords = "visual analytics, weather forecasting, uncertainty"
}@ARTICLE {Stoppel-2017-VPI,
author = "Sergej Stoppel and Stefan Bruckner",
title = "Vol²velle: Printable Interactive Volume Visualization",
journal = "IEEE Transactions on Visualization and Computer Graphics",
year = "2017",
volume = "23",
number = "1",
pages = "861--870",
month = "jan",
abstract = "Interaction is an indispensable aspect of data visualization. The
presentation of volumetric data, in particular, often significantly
benefits from interactive manipulation of parameters such as transfer
functions, rendering styles, or clipping planes. However, when we
want to create hardcopies of such visualizations, this essential
aspect is lost. In this paper, we present a novel approach for creating
hardcopies of volume visualizations which preserves a certain degree
of interactivity. We present a method for automatically generating
Volvelles, printable tangible wheel charts that can be manipulated
to explore different parameter settings. Our interactive system allows
the flexible mapping of arbitrary visualization parameters and supports
advanced features such as linked views. The resulting designs can
be easily reproduced using a standard printer and assembled within
a few minutes.",
pdf = "pdfs/Stoppel-2017-VPI.pdf",
images = "images/Stoppel-2017-VPI.jpg",
thumbnails = "images/Stoppel-2017-VPI.png",
youtube = "https://www.youtube.com/watch?v=Z1K8t-FCiXI",
doi = "10.1109/TVCG.2016.2599211",
event = "IEEE SciVis 2016",
keywords = "physical visualization, interaction, volume visualization, illustrative visualization",
location = "Baltimore, USA"
}@ARTICLE {Solteszova-2017-OFS,
author = "Veronika \v{S}olt{\'e}szov{\'a} and {\AA}smund Birkeland and Sergej Stoppel and Ivan Viola and Stefan Bruckner",
title = "Output-Sensitive Filtering of Streaming Volume Data",
journal = "Computer Graphics Forum",
year = "2017",
volume = "36",
number = "1",
pages = "249--262",
month = "jan",
abstract = "Real-time volume data acquisition poses substantial challenges for
the traditional visualization pipeline where data enhancement is
typically seen as a pre-processing step. In the case of 4D ultrasound
data, for instance, costly processing operations to reduce noise
and to remove artifacts need to be executed for every frame. To enable
the use of high quality filtering operations in such scenarios, we
propose an output-sensitive approach to the visualization of streaming
volume data. Our method evaluates the potential contribution of all
voxels to the final image, allowing us to skip expensive processing
operations that have little or no effect on the visualization. As
filtering operations modify the data values which may affect the
visibility, our main contribution is a fast scheme to predict their
maximum effect on the final image. Our approach prioritizes filtering
of voxels with high contribution to the final visualization based
on a maximal permissible error per pixel. With zero permissible error,
the optimized filtering will yield a result identical to filtering
of the entire volume. We provide a thorough technical evaluation
of the approach and demonstrate it on several typical scenarios that
require on-the-fly processing.",
pdf = "pdfs/Solteszova-2017-OFS.pdf",
images = "images/Solteszova-2017-OFS.jpg",
thumbnails = "images/Solteszova-2017-OFS.png",
youtube = "https://www.youtube.com/watch?v=xGPs560ttp0",
doi = "10.1111/cgf.12799",
keywords = "output-sensitive processing, volume data, filtering"
}