@misc{Hauser2011Dagstuhl,
 author = {Helwig Hauser},
 title = {Helwig Hauser on Interactive Visual Analysis of Multi-Dimensional Scientific Data},
 year = {2011},
 month = {June},
 howpublished = {Invited talk at the Dagstuhl Seminar on Scientific Visualization in Dagstuhl, Germany.},
 abstract = { Invited talk at the Dagstuhl Seminar on Scientific Visualization in Dagstuhl, Germany.},
 images = {images/2011-06-06--Dagstuhl--MultiDimSciDataIVA--print--new--2up_Image_0001.jpg, images/2011-06-06--Dagstuhl--MultiDimSciDataIVA--print--new--2up_Image_0002.jpg, images/2011-06-06--Dagstuhl--MultiDimSciDataIVA--print--new--2up_Image_0002(2).jpg, images/2011-06-06--Dagstuhl--MultiDimSciDataIVA--print--new--2up_Image_0004.jpg},
 thumbnails = {images/2011-06-06--Dagstuhl--MultiDimSciDataIVA--print--new--2up_Image_0001(2).jpg},
 pdf = {pdfs/2011-06-06--Dagstuhl--MultiDimSciDataIVA--print--new--2up.pdf},
}

@phdthesis{lampe11thesis,
  title = {Interactive Visual Analysis of Process Data},
  author = {Ove Daae Lampe},
  year = {2011},
  abstract = {Data gathered from processes, or process data, contains many different aspects
that a visualization system should also convey. Aspects such as, temporal
coherence, spatial connectivity, streaming data, and the need for in-situ
visualizations, which all come with their independent challenges. Additionally,
as sensors get more affordable, and the benefits of measurements get clearer we
are faced with a deluge of data, of which sizes are rapidly growing. With all
the aspects that should be supported and the vast increase in the amount of
data, the traditional techniques of dashboards showing the recent data becomes
insufficient for practical use. In this thesis we investigate how to extend the traditional
process visualization techniques by bringing the streaming process data
into an interactive visual analysis setting. The augmentation of process visualization
with interactivity enables the users to go beyond the mere observation,
pose questions about observed phenomena and delve into the data to mine for
the answers. Furthermore, this thesis investigates how to utilize frequency based,
as opposed to item based, techniques to show such large amounts of data. By
utilizing Kernel Density Estimates (KDE) we show how the display of streaming
data benefit by the non-parametric automatic aggregation to interpret incoming
data put in context to historic data.},
  school = {Department of Informatics, University of Bergen, Norway},
  month = {Sep},
  ISBN = {978-82-308-1910-4},
  images = {images/lampe11thesis.png},
  thumbnails = {images/lampe11thesis_thumb.png},
  pdf = {pdfs/lampe11thesis.pdf},
}


@misc{Lueks11Spatially,
 author = {Wouter Lueks and Ivan Viola and Matthew van der Zwan and Henk Bekker
  and Tobias Isenberg},
 title  ={Spatially Continuous Change of Abstraction in Molecular Visualization},
 year = {2011},
 howpublished = {BioVis 2011 - Abstract track},
 location = {Providence, RI},
 abstract = {Based on an approach for the temporal change of abstraction in
  molecular visualization we describe how to achieve a spatially explicit
  control of abstraction. This allows us to depict different abstraction
  stages of a single molecule in a single still-image visualization.
  This approach works best for long, linear molecules with
  repeating substructures that allow viewers to visually compare the
  continuous representational changes of these parts.},
 url = {http://www.cs.rug.nl/~isenberg/VideosAndDemos/Zwan2011IMV},
 notes = {Best Abstract award},
 vid = {https://www.youtube.com/watch?v=1ANKp9mMFvo},
 images = {images/Lueks11Spatially01.jpg, images/Lueks11Spatially02.jpg, images/Lueks11Spatially03.jpg},
 thumbnails = {images/Lueks11Spatially01_thumb.jpg, images/Lueks11Spatially02_thumb.jpg, images/Lueks11Spatially03_thumb.jpg},
}

@article{Matkovic11InteractiveVisual,
  author = {Kresimir Matkovic and Denis Gracanin and Mario Jelovic and Helwig Hauser},
  title = {Interactive Visual Analysis Supporting Design, Tuning, and Optimization of Diesel Engine Injection},
  year = {2011},
  journal = {Proceedings of IEEE Visualization 2011 (Discovery Exhibition)},
  abstract = {Design and optimization of modern, complex systems is unimaginable
   without simulation. Although the design goals are known in advance, finding
   an optimal combination of input parameters is a long and tedious task.
   Simulation of car engine injection systems is a relatively short process.
   It is possible to run many simulations and then to explore the parameter
   space. Efficient tools and techniques for parameter space exploration and
   optimization are needed. We have developed an interactive visual analysis
   tool, ComVis, and related techniques. We illustrate how ComVis is used to
   explore the parameter space and to tune and optimize car engine injection
   systems. The collaboration between domain experts and visualization experts
   resulted in a new workflow for injection system design, and in development
   of new, commercially available tools.},  
  url = {http://www.discoveryexhibition.org/pmwiki.php/Entries/2011Matkovic},
  images = {images/Matkovic11InteractiveVisual01.png, Matkovic11InteractiveVisual02.png, Matkovic11InteractiveVisual03.png},
  thumbnails = {images/Matkovic11InteractiveVisual_thumb.png},
}

@article{Matkovic11CurrentTrends,
 title = {Current Trends for 4D Space-Time Topology for Semantic Flow Segmentation},
 journal = {Procedia Computer Science},
 author = {Kresimir Matkovic and Alan Lez and Helwig Hauser and Armin Pobitzer 
  and Holger Theisel and Alexander Kuhn and Mathias Otto and Ronald Peikert and 
  Benjamin Schindler and Raphael Fuchs},
 abstract = {Recent advances in computing and simulation technology promote the simulation of
  time-dependent flows, i.e., flows where the velocity field changes over time. The simulation
  of time-dependent flow is a more realistic approximation of natural phenomena and it
  represents an invaluable tool for scientists and practitioners in multiple disciplines,
  including meteorology, vehicle design, and medicine. Flow visualization, a subfield of
  scientific visualization, is one of several research areas which deal with the analysis of
  flows. There are many methods for the analysis of steady flows, but the extension to the
  time-dependent case is not straight forward. The SemSeg project, a FET-Open project in the
  7th Framework programme, attempts to provide a solution for the semantic segmentation of
  time-dependent flows. It aims at the formulation of a sound theoretical mechanism to describe
  structural features in time-dependent flow. In this paper, we briefly summarize recent
  research results from the SemSeg project. Several different approaches are pursued in
  the project, including methods based on the finite-time Lyapunov exponent (FTLE), methods based
  on vector field topology (VFT), and interactive visual analysis (IVA) methods. Uncertainty
  visualization and the interactive evaluation of methods are helping in evaluating the results.},
 volume = {7},
 number = {0},
 pages = {253--255},
 year = {2011},
 note = {<ce:title>Proceedings of the 2nd European Future Technologies
         Conference and Exhibition 2011 (FET 11)</ce:title>},
 issn = {1877-0509},
 doi = {10.1016/j.procs.2011.09.013},
 url = {http://www.sciencedirect.com/science/article/pii/S1877050911005734},
 images = {images/Matkovic11CurrentTrends.png},
 thumbnails = {images/Matkovic11CurrentTrends_thumb.png},
}

@inproceedings{lampe11modelbuilding,
  author = {Ove Daae Lampe and Helwig Hauser },
  title = { Model Building in Visualization Space },
  booktitle = {Proceedings of Sigrad 2011 },
  location = {Stockholm, Sweeden},
  year = {2011},
  abstract = {Researching formal models that explain selected natural 
  phenomena of interest is a central aspect of most scientific work. 
  A tested and confirmed model can be the key to classification,
  knowledge crystallization, and prediction.With this paper we propose 
  a new approach to rapidly draft, fit and quantify model prototypes in 
  visualization space. We also show that these models can provide 
  important insights and accurate metrics about the original data. 
  Using our technique, which is similar to the statistical concept of 
  de-trending, data that behaves according to the model is de-emphasized, 
  leaving only outliers and potential model flaws for further inspection. 
  Moreover, we provide several techniques to assist the user in the 
  process of prototyping such models. We demonstrate the usability of 
  this approach in the context of the analysis of streaming process 
  data from the Norwegian oil and gas industry, and on weather data, 
  investigating the distribution of temperatures over the course of a year.},
  pdf = {pdfs/lampe11sigrad.pdf},
  url = {http://www.ep.liu.se/ecp_article/index.en.aspx?issue=065;article=007},
  images = {images/lampe11sigrad.jpg},
  thumbnails = {images/lampe11sigrad_thumb.jpg},
  pres = {http://folk.uib.no/ola062/sigrad2011/},
  project = {elad},
}

@article{turkay11brushingDimensions,
  author = {Cagatay Turkay and Peter Filzmoser and Helwig Hauser},
  title = {Brushing Dimensions -- A Dual Visual Analysis Model for 
High-dimensional Data},
  year = {2011},
  abstract = {In many application fields, data analysts have to deal with 
datasets that contain many expressions per item. The effective analysis
of such multivariate datasets is dependent on the user’s ability to 
understand both the intrinsic dimensionality of the dataset as well as 
the distribution of the dependent values with respect to the dimensions. 
In this paper, we propose a visualization model that enables the joint 
interactive visual analysis of multivariate datasets with respect to 
their dimensions as well as with respect to the actual data values. We 
describe a dual setting of visualization and interaction in items space 
and in dimensions space. The visualization of items is linked to the 
visualization of dimensions with brushing and focus+context 
visualization. With this approach, the user is able to jointly study the 
structure of the dimensions space as well as the distribution of data 
items with respect to the dimensions. Even though the proposed 
visualization model is general, we demonstrate its application in the 
context of a DNA microarray data analysis.},
  journal = {IEEE Transactions on Visualization and Computer Graphics},
  volume = {17},
  number = {12},
  pages = {2591--2599},
  event = {IEEE Information Visualization Conference 2011},
  location = {Providence, RI, USA},
  URL = {http://dx.doi.org/10.1109/TVCG.2011.178},
  images = {images/turkay11dimensions.png, images/turkay11dimensions3.png, images/turkay11dimensions2.png},
  thumbnails = {images/turkay11dimensions_thumb.png, images/turkay11dimensions3_thumb.png, images/turkay11dimensions2_thumb.png},
}

@article{angelelli11straightening,
  author = {Paolo Angelelli and Helwig Hauser},
  title = {Straightening Tubular Flow for Side-by-Side Visualization},
  year = {2011},
  abstract = {Flows through tubular structures are common in many fields, 
including blood flow in medicine and tubular fluid flows in engineering.
The analysis of such flows is often done with a strong reference to the 
main flow direction along the tubular boundary. In this paper we present 
an approach for straightening the visualization of tubular flow. By 
aligning the main reference direction of the flow, i.e., the center line
of the bounding tubular structure, with one axis of the screen, we are 
able to natively juxtapose (1.) different visualizations of the same flow,
either utilizing different flow visualization techniques, or by varying 
parameters of a chosen approach such as the choice of seeding locations
for integration-based flow visualization, (2.) the different time steps 
of a time-dependent flow, (3.) different projections around the 
center line, and (4.) quantitative flow visualizations in immediate 
spatial relation to the more qualitative classical flow visualization. 
We describe how to utilize this approach for an informative interactive 
visual analysis. We demonstrate the potential of our approach by 
visualizing two datasets from two different fields: an arterial blood flow 
measurement and a tubular gas flow simulation from the automotive industry.},
  journal = {IEEE Transactions on Visualization and Computer Graphics},
  volume = {17},
  number = {12},
  pages = {2063--2070},
  event = {IEEE Visualization Conference 2011},
  location = {Providence, RI, USA},
  URL = {http://dx.doi.org/10.1109/TVCG.2011.235},
  images = {images/angelelli11straightening1.jpg, images/angelelli11straightening2.jpg},
  thumbnails = {images/angelelli11straightening1_thumb.jpg, images/angelelli11straightening2_thumb.jpg},
  pdf = {pdfs/angelelli11straightening.pdf},
  vid = {http://www.ii.uib.no/vis/publications/vids/angelelli11TubularFlowStraightening.wmv}
}

@article{ruiz11automaticTFs,
  author = {Marc Ruiz and Anton Bardera and Imma Boada and Ivan Viola and 
  Miquel Feixas and Mateu Sbert},
  title = {Automatic Transfer Functions based on Informational Divergence},
  year = {2011},
  abstract = {In this paper we present a framework to define transfer 
functions from a target distribution provided by the user. A target
distribution can reflect the data importance, or highly relevant 
data value interval, or spatial segmentation. Our approach is based
on a communication channel between a set of viewpoints and a set of 
bins of a volume data set, and it supports 1D as well as 2D transfer 
functions including the gradient information. The transfer functions 
are obtained by minimizing the informational divergence or 
Kullback-Leibler distance between the visibility distribution 
captured by the viewpoints and a target distribution selected by the 
user. The use of the derivative of the informational divergence 
allows for a fast optimization process. Different target 
distributions for 1D and 2D transfer functions are analyzed together 
with importance-driven and view-based techniques.},
  journal = {IEEE Transactions on Visualization and Computer Graphics},
  volume = {17},
  number = {12},
  pages = {1932--1941},
  event = {IEEE Visualization Conference 2011},
  location = {Providence, RI, USA},
  images = {images/ruiz11automaticTFs1.jpg, images/ruiz11automaticTFs2.jpg, images/ruiz11automaticTFs3.jpg, images/ruiz11automaticTFs4.jpg},
  thumbnails = {images/ruiz11automaticTFs1_thumb.jpg, images/ruiz11automaticTFs2_thumb.jpg, images/ruiz11automaticTFs3_thumb.jpg, images/ruiz11automaticTFs4_thumb.jpg},
  project = {illustrasound},
}

@article{pobitzer11topology,
  title = {The State of the Art in Topology-based Visualization of Unsteady Flow},
  author = {Armin Pobitzer and Ronald Peikert and Raphael Fuchs and 
  Benjamin Schindler and Alexander Kuhn and Holger Theisel and 
  Kresimir Matkovic and Helwig Hauser},
  month = {September},
  year = {2011},
  abstract = {Vector fields are a common concept for the representation of 
many different kinds of flow phenomena in science and engineering. Methods 
based on vector field topology are known for their convenience for visualizing 
and analyzing steady flows, but a counterpart for unsteady flows is still 
missing. However, a lot of good and relevant work aiming at such a solution 
is available.
We give an overview of previous research leading towards topology-based and 
topology-inspired visualization of unsteady flow, pointing out the different 
approaches and methodologies involved as well as their relation to each other, 
taking classical (i.e., steady) vector field topology as our starting point. 
Particularly, we focus on Lagrangian methods, space-time domain approaches, 
local methods, and stochastic and multi-field approaches. Furthermore, we 
illustrate our review with practical examples for the different approaches.},
  journal = {Computer Graphics Forum},
  volume = {30},
  number = {6},
  pages = {1789--1811},
  images = {images/pobitzer10topology.jpg,},
  thumbnails = {images/pobitzer10topology_thumb.jpg},
  project = {semseg},
  URL = {http://dx.doi.org/10.1111/j.1467-8659.2011.01901.x}
}

@incollection{oye11illustrativeCouinaud,
 author = {Ola Kristoffer {\O}ye and Dag Magne Ulvang and Odd Helge Gilja and Helwig Hauser and Ivan Viola},
 title = {Illustrative Couinaud Segmentation for Ultrasound Liver Examinations},
 booktitle = {Smart Graphics},
 series = {Lecture Notes in Computer Science},
 publisher = {Springer Berlin / Heidelberg},
 isbn = {978-3-642-22570-3},
 pages = {60--77},
 volume = {6815},
 url = {http://dx.doi.org/10.1007/978-3-642-22571-0_6},
 abstract = {Couinaud segmentation is a widely used liver partitioning scheme for 
describing the spatial relation between diagnostically relevant anatomical and 
pathological features in the liver. In this paper, we propose a new methodology
for effectively conveying these spatial relations during the ultrasound 
examinations. We visualize the two-dimensional ultrasound slice in the context 
of a three-dimensional Couinaud partitioning of the liver. The partitioning is 
described by planes in 3D reflecting the vascular tree anatomy, specified in the 
patient by the examiner using her natural interaction tool, i.e., the ultrasound 
transducer with positional tracking. A pre-defined generic liver model is adapted 
to the specified partitioning in order to provide a representation of the 
patient’s liver parenchyma. The specified Couinaud partitioning and parenchyma 
model approximation is then used to enhance the examination by providing visual 
aids to convey the relationships between the placement of the ultrasound plane 
and the partitioned liver. The 2D ultrasound slice is augmented with Couinaud 
partitioning intersection information and dynamic label placement. A linked 
3D view shows the ultrasound slice, cutting the liver and displayed using fast 
exploded view rendering. The described visual augmentation has been characterized 
by the clinical personnel as very supportive during the examination procedure, 
and also as a good basis for pre-operative case discussions.},
 year = {2011},
 images = {images/oye11illustrativeCouinaud1.jpg, images/oye11illustrativeCouinaud2.jpg, images/oye11illustrativeCouinaud3.jpg},
 thumbnails = {images/oye11illustrativeCouinaud1_thumb.jpg, images/oye11illustrativeCouinaud2_thumb.jpg, images/oye11illustrativeCouinaud3_thumb.jpg},
 project = {illustrasound,medviz,illvis} 
}

@inproceedings{palmerius11ultrasoundPalpation,
 author={Karljohan Lundin Palmerius and Roald Flesland Havre and Odd Helge Gilja and Ivan Viola},
 booktitle={Proc. International Symposium on Computer-Based Medical Systems (CBMS)},
 location = {Bristol, UK},
 title={Ultrasound palpation by haptic elastography},
 year={2011},
 month={june},
abstract={Palpation is an important method in the medical physical examination.
Surface palpation alone, however, cannot be used in many situations due to the 
anatomical positions. Elastography images are therefore in many cases a 
complement to other imaging modalities. In this article we present a method 
for providing haptic feedback from elastography imaging data, allowing 
palpation of the hardness data. A prototype implementation was used in a 
demonstration session with domain experts providing feedback on the presented 
algorithm and also on the basic principle of palpating data from 
elastography imaging.},
 url={http://dx.doi.org/10.1109/CBMS.2011.5999154},
 images = {images/palmerius11ultrasoundPalpation.jpg},
 thumbnails = {images/palmerius11ultrasoundPalpation_thumb.jpg},
  project = {illustrasound,medviz,illvis}
}

@inproceedings{solteszova11chromatic,
 title =  {Chromatic Shadows for Improved Perception},
 author = {Veronika \v{S}olt{\'e}szov{\'a} and Daniel Patel and Ivan Viola},
 booktitle = {Proc. Non-photorealistic Animation and Rendering (NPAR 2011)},
 year =  {2011},
 pages =  {105--115},
 abstract = {Soft shadows are effective depth and shape cues. However, 
traditional shadowing algorithms decrease the luminance in shadow
areas. The features in shadow become dark and thus shadowing causes
information hiding. For this reason, in shadowed areas, medical 
illustrators decrease the luminance less and compensate the lower 
luminance range by adding color, i.e., by introducing a chromatic 
component. This paper presents a novel technique which enables an 
interactive setup of an illustrative shadow representation for 
preventing overdarkening of important structures. We introduce a 
scalar attribute for every voxel denoted as shadowiness and propose 
a shadow transfer function that maps the shadowiness to a color and 
a blend factor. Typically, the blend factor increases linearly with 
the shadowiness. We then let the original object color blend with 
the shadow color according to the blend factor. We suggest a 
specific shadow transfer function, designed together with a medical 
illustrator which shifts the shadow color towards blue. This shadow 
transfer function is quantitatively evaluated with respect to 
relative depth and surface perception.},
 location = {Vancouver, Canada},
 url = {http://dx.doi.org/10.1145/2024676.2024694},
 images = {images/solteszova11chromatic3.jpg, images/solteszova11chromatic2.jpg, images/solteszova11chromatic.jpg, images/solteszova11chromatic4.jpg},
 thumbnails = {images/solteszova11chromatic3_thumb.jpg, images/solteszova11chromatic2_thumb.jpg, images/solteszova11chromatic_thumb.jpg, images/solteszova11chromatic4_thumb.jpg},
 project = {illustrasound,medviz,illvis}
}

@inproceedings{schaefer11registration,
 title =  {Registration of ultrasonography sequences based on temporal regions},
 author = {Sebastian Sch{\"a}fer and Paolo Angelelli and Kim Nylund and Odd Helge Gilja and Klaus T{\"o}nnies},
 booktitle = {Proc. Intl. Symp. Image and Signal Processing and Analysis (ISPA)},
 year =  {2011},
 pages =  {749--754},
 abstract = {2D Ultrasonography images with parallel contrast enhanced 
 sequences for analysis constitute a rapid and inexpensive imaging 
 technique with high temporal resolution to assess perfusion of tissue. 
 However, motion from various influences corrupts the inter-pixel 
 correspondences between different time frames and therefore hampers 
 computer-assisted analysis of perfusion parameters. We present a 
 user-supported method applying a temporal similarity matrix to remove 
 frames with uncorrectable out-of-plane motion. For the remaining 
 regions of frames, motion influence can be compensated for by image 
 registration. Subsequently B-Spline based registration is applied 
 using the temporal regions with automatic determination of a suitable 
 reference frame image. Evaluation with ground truth data of six 
 datasets comparing a medical expert frame analysis to the proposed 
 technique yields 85.1% sensitivity and 81.7% specificity in average. 
 On average 6% of the frames have been erroneously included in temporal 
 regions, although they contain out-of-plane motion.},
 location = {Dubrovnik, Croatia},
 url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6046702},
 pdf = {pdfs/schaefer11Registration.pdf},
 images = {images/schaefer11registration.jpg},
 thumbnails = {images/schaefer11registration_thumb.jpg}
}

@article{kehrer11heterogeneous,
  author = {Johannes Kehrer and Philipp Muigg and 
			Helmut Doleisch and Helwig Hauser},
  title = {Interactive Visual Analysis of Heterogeneous Scientific Data across an Interface},
  year = {2011},
  abstract = {We present a systematic approach to the interactive visual analysis 
of heterogeneous scientific data. The data consists of two interrelated parts 
given on spatial grids over time (e.g., atmosphere and ocean part from a coupled 
climate model). By integrating both data parts in a framework of coordinated 
multiple views (with linking and brushing), the joint investigation of features 
across the data parts is enabled. An interface is constructed between the data 
parts that specifies (a) which grid cells in one part are related to grid cells 
in the other part, and vice versa, (b) how selections (in terms of feature 
extraction via brushing) are transferred between the two parts, and (c) how an 
update mechanism keeps the feature specification in both data parts consistent
during the analysis. We also propose strategies for visual analysis that result 
in an iterative refinement of features specified across both data parts. Our approach 
is demonstrated in the context of a complex simulation of fluid--structure interaction 
and a multi-run climate simulation.},
  journal = {IEEE Transactions on Visualization and Computer Graphics},
  volume = {17},
  number = {7},
  pages = {934--946},
  event = {IEEE VisWeek 2011},
  location = {Providence, RI, USA},  
  url = {http://dx.doi.org/10.1109/TVCG.2010.111},
  pdf = {pdfs/kehrer11heterogeneous.pdf},
  vid = {vids/kehrer11heterogeneous.html},
  images = {images/kehrer11heterogeneous2.jpg, images/kehrer11heterogeneous3.jpg, images/kehrer11heterogeneous0.jpg, images/kehrer11heterogeneous1.jpg},
  thumbnails = {images/kehrer11heterogeneous2_thumb.jpg, images/kehrer11heterogeneous3_thumb.jpg, images/kehrer11heterogeneous0_thumb.jpg, images/kehrer11heterogeneous1_thumb.jpg},
}

@article{lampe11curveDensity,
  author = {Ove Daae Lampe and Helwig Hauser},
  title = {Curve Density Estimates},
  year = {2011},
abstract = {In this work, we present a technique based on kernel density 
estimation for rendering smooth curves. With this approach, we produce 
uncluttered and expressive pictures, revealing frequency information 
about one, or, multiple curves, independent of the level of detail in the 
data, the zoom level, and the screen resolution. With this technique the 
visual representation scales seamlessly from an exact line drawing, 
(for low-frequency/low-complexity curves) to a probability density 
estimate for more intricate situations. This scale-independence 
facilitates displays based on non-linear time, enabling high-resolution 
accuracy of recent values, accompanied by long historical series for
context. We demonstrate the functionality of this approach in the 
context of prediction scenarios and in the context of streaming data.},
  journal = {Computer Graphics Forum},
  volume = {30},
  number = {3},
  pages = {633--642},
  url = {http://dx.doi.org/10.1111/j.1467-8659.2011.01912.x},
  event = {EuroVis 2011},
  location = {Bergen, Norway},  
  images = {images/lampe11curveDensity3.jpg, images/lampe11curveDensity1.jpg, images/lampe11curveDensity2.jpg},
  thumbnails = {images/lampe11curveDensity3_thumb.jpg, images/lampe11curveDensity1_thumb.jpg, images/lampe11curveDensity2_thumb.jpg},
  project = {elad},
}

@article{turkay11temporalCluster,
  author = {Cagatay Turkay and Julius Parulek and Nathalie Reuter and Helwig Hauser},
  title = {Interactive Visual Analysis of Temporal Cluster Structures},
  year = {2011},
abstract = {Cluster analysis is a useful method which reveals underlying 
structures and relations of items after grouping them into clusters. In 
the case of temporal data, clusters are defined over time intervals where 
they usually exhibit structural changes. Conventional cluster analysis 
does not provide sufficient methods to analyze these structural changes, 
which are, however, crucial in the interpretation and evaluation of 
temporal clusters. In this paper, we present two novel and interactive 
visualization techniques that enable users to explore and interpret the 
structural changes of temporal clusters. We introduce the temporal 
cluster view, which visualizes the structural quality of a number of 
temporal clusters, and temporal signatures, which represents the structure 
of clusters over time. We discuss how these views are utilized to 
understand the temporal evolution of clusters. We evaluate the proposed
techniques in the cluster analysis of mixed lipid bilayers.},
  journal = {Computer Graphics Forum},
  volume = {30},
  number = {3},
  pages = {711--720},
  url = {http://dx.doi.org/10.1111/j.1467-8659.2011.01920.x},  
  event = {EuroVis 2011},
  location = {Bergen, Norway},  
  images = {images/turkay11temporal1.jpg, images/turkay11temporal2.jpg, images/turkay11temporal3.jpg},
  thumbnails = {images/turkay11temporal1_thumb.jpg, images/turkay11temporal2_thumb.jpg, images/turkay11temporal3_thumb.jpg},
}

@article{pobitzer11energyScale,
  author = {Armin Pobitzer and Murat Tutkun and {\O}yvind 
  Andreassen and Raphael Fuchs and Ronald Peikert and Helwig Hauser},
  title = {Energy-scale Aware Feature Extraction for Flow Visualization},
  year = {2011},
abstract = {In the visualization of flow simulation data, feature detectors 
often tend to result in overly rich response, making some sort of filtering 
or simplification necessary to convey meaningful images. In this paper we 
present an approach that builds upon a decomposition of the flow field 
according to dynamical importance of different scales of motion energy. 
Focusing on the high-energy scales leads to a reduction of the flow field 
while retaining the underlying physical process. The presented method 
acknowledges the intrinsic structures of the flow according to its energy 
and therefore allows to focus on the energetically most interesting aspects 
of the flow. Our analysis shows that this approach can be used for methods 
based on both local feature extraction and particle integration and we 
provide a discussion of the error caused by the approximation. Finally, 
we illustrate the use of the proposed approach for both a local and a global 
feature detector and in the context of numerical flow simulations.},
  journal = {Computer Graphics Forum},
  volume = {30},
  number = {3},
  pages = {771--780},
  url = {http://dx.doi.org/10.1111/j.1467-8659.2011.01926.x},
  event = {EuroVis 2011},
  location = {Bergen, Norway},
  images = {images/pobitzer11energyScale1.jpg, images/pobitzer11energyScale3.jpg, images/pobitzer11energyScale2.jpg},
  thumbnails = {images/pobitzer11energyScale1_thumb.jpg, images/pobitzer11energyScale3_thumb.jpg, images/pobitzer11energyScale2_thumb.jpg},
  project = {semseg}
}

@inproceedings{pobitzer11semseg,
 title =  {The {SemSeg} project and recent developments in flow visualization},
 author =  {Armin Pobitzer and Helwig Hauser},
 booktitle = {Proc. Sixth National Conference on Computational Mechanics (MekIT'11)},
 year =  {2011},
 editors =  {B. Skallerud and H.I. Andersson},
 pages =  {281--292},
 abstract = {The present paper discusses recent efforts to develop semantic 
segmentation of spacetime flow domains for visualization purposes, taking the
work of the SemSeg project as a starting point. In particular we address 
separation structures based on Finite-time Lyapunov exponents and their 
extraction, the incorporation of uncertainty, and the application of 
Interactive Visual Analysis in the context of flow visualization.},
 publisher  = {Tapir Academic Press},
 address =  {Trondheim, Norway},
 month = {May},
 images = {images/pobitzer11semseg.jpg},
 thumbnails = {images/pobitzer11semseg_thumb.jpg},
 project = {semseg}
}

@phdthesis{kehrer11thesis,
  title = {Interactive Visual Analysis of Multi-faceted Scientific Data},
  author = {Johannes Kehrer},
  year = {2011},
  abstract = {Visualization plays an important role in exploring, analyzing
and presenting large and heterogeneous scientific data that arise in many 
disciplines of medicine, research, engineering, and others. We can see that 
model and data scenarios are becoming increasingly multi-faceted: data are 
often multi-variate and time-dependent, they stem from different data sources 
(multi-modal data), from multiple simulation runs (multi-run data), or from 
multi-physics simulations of interacting phenomena that consist of coupled 
simulation models (multi-model data). The different data characteristics 
result in special challenges for visualization research and interactive 
visual analysis. The data are usually large and come on various types of 
grids with different resolution that need to be fused in the visual analysis.

This thesis deals with different aspects of the interactive visual analysis 
of multi-faceted scientific data. The main contributions of this thesis are: 
1) a number of novel approaches and strategies for the interactive visual 
analysis of multi-run data; 2) a concept that enables the feature-based visual 
analysis across an interface between interrelated parts of heterogeneous 
scientific data (including data from multi-run and multi-physics simulations); 
3) a model for visual analysis that is based on the computation of traditional
and robust estimates of statistical moments from higher-dimensional multi-run 
data; 4) procedures for visual exploration of time-dependent climate data that 
support the rapid generation of promising hypotheses, which are subsequently 
evaluated with statistics; and 5) structured design guidelines for glyph-based 
3D visualization of multi-variate data together with a novel glyph. All these 
approaches are incorporated in a single framework for interactive visual analysis 
that uses powerful concepts such as coordinated multiple views, feature 
specification via brushing, and focus+context visualization. Especially the data 
derivation mechanism of the framework has proven to be very useful for analyzing 
different aspects of the data at different stages of the visual analysis. The 
proposed concepts and methods are demonstrated in a number of case studies that 
are based on multi-run climate data and data from a multi-physics simulation.},
  school = {Department of Informatics, University of Bergen, Norway},
  month = {Mar},
  URL = {http://www.ii.UiB.no/vis/team/kehrer/thesis/},
  ISBN = {978-82-308-1733-9},
  images = {images/kehrer11thesis.jpg, images/kehrer11heterogeneous1.jpg, images/kehrer08vis01.jpg, images/kehrer11thesis1.png},
  thumbnails = {images/kehrer11thesis_thumb.jpg, images/kehrer11heterogeneous1_thumb.jpg, images/kehrer08vis01_thumb.jpg, images/kehrer11thesis1_thumb.png},
  pdf = {pdfs/kehrer11thesis.pdf},
}

@inproceedings{turkay11cluster,
  author = {Cagatay Turkay and Julius Parulek and Nathalie Reuter and Helwig Hauser},
  title = {Integrating Cluster Formation and Cluster Evaluation in 
Interactive Visual Analysis},
  booktitle = {Proc. Spring Conference on Computer Graphics (SCCG 2011) -- second best paper},
  pages = {??--??},
  year = {2011},
  abstract = {Cluster analysis is a popular method for data investigation where
data items are structured into groups called clusters. This analysis
involves two sequential steps, namely cluster formation and cluster
evaluation. In this paper, we propose the tight integration of cluster
formation and cluster evaluation in interactive visual analysis in order
to overcome the challenges that relate to the black-box nature of
clustering algorithms. We present our conceptual framework in the
form of an interactive visual environment. In this realization of our
framework, we build upon general concepts such as cluster comparison,
clustering tendency, cluster stability and cluster coherence.
Additionally, we showcase our framework on the cluster analysis of
mixed lipid bilayers.},
  location = {Budmerice, Slovakia}, 
  images = {images/turkay11cluster2.jpg, images/turkay11cluster1.jpg, images/turkay11cluster3.jpg},
  thumbnails = {images/turkay11cluster2_thumb.jpg, images/turkay11cluster1_thumb.jpg, images/turkay11cluster3_thumb.jpg},
  pdf = {pdfs/turkay11cluster.pdf},  
}

@inproceedings{florekHauser11modeTree,
  author = {Martin Florek and Helwig Hauser},
  title = {Interactive Bivariate Mode Trees for Visual Structure Analysis},
  booktitle = {Proceedings of the Spring Conference on Computer Graphics (SCCG 2011)},
  pages = {??--??},
  year = {2011},
  abstract = {The number of modes in a kernel density estimation of a certain
data distribution is strongly dependent on the chosen scale parameter.
In this paper, we present an interactive mode tree visualization
that allows to visually analyze the modality structure of a data
distribution. Due to the branched structure of the bivariate mode
tree, composed of many curved arcs in 3D, we need to utilize advanced
techniques, including clutter removal through transparency,
on demand outlier suppression or preservation, and best views, to
improve the legibility of the visualization mapping.},
  location = {Budmerice, Slovakia}, 
  images = {images/florekHauser11modeTree.jpg, images/florekHauser11modeTree2.jpg},
  thumbnails = {images/florekHauser11modeTree_thumb.jpg, images/florekHauser11modeTree2_thumb.jpg}, 
}

@inproceedings{patel11apprenticeship,
  author = {Daniel Patel and Stefan Bruckner and M. Eduard Gr{\"o}ller},
  title = {PhD Education Through Apprenticeship},
  year = {2011},
  abstract = {We describe and analyze the PhD education in the visualization group 
at the Vienna University of Technology and set the education in a larger perspective. 
Four central mechanisms drive the PhD education in Vienna. They are: to require an 
article-based PhD; to give the student freedom to choose research direction; 
to let students work in shared offices towards joint deadlines; and to involve 
students in reviewing articles. This paper describes these mechanisms in detail and 
illustrates their effect.},
  booktitle = {Eurographics Conference 2011 Education Papers},
  pages = {23--28},
  event = {Eurographics 2011},
  location = {Llandudno, UK},
  images = {images/patel11apprenticeship.jpg},
  thumbnails = {images/patel11apprenticeship_thumb.jpg}, 
}

@inproceedings{lez11pathlines,
  author = {Alan Lez and Andreas Zajic and Kresimir Matkovic and Armin 
  Pobitzer and Michael Mayer and Helwig Hauser},
  title = {Interactive Exploration and Analysis of Pathlines in Flow Data},
  year = {2011},
  abstract = {The rapid development of large-scale scientific computing nowadays 
allows to inherently respect the unsteady character of natural phenomena in 
computational flow simulation. With this new trend to more regularly consider 
time-dependent flow scenarios, an according new need for advanced exploration 
and analysis solutions emerges. In this paper, we now present three new 
concepts in pathline analysis which further improve the abilities of analysis: 
a multi-step analysis which helps to save time and space needed for computation, 
direct pathline brushing, and usage of pre-configured view arrangements. We have 
found that clever combining of these three concepts with already existing 
methods creates very powerful tool for pathline analysis. The coordinated 
multiple views (CMV) tool used supports iterative composite brushing which 
enables a quick information drill-down. We illustrate the usefulness using an 
example from the automotive industry. We have analyzed an exhaust manifold
time-dependent simulation data set.},
  booktitle = {Proc. International Conference in Central Europe on Computer
Graphics, Visualization and Computer Vision (WSCG 2011)},
  pages = {17--24},
  location = {Plzen, Czech Republic},
  images = {images/lez11pathlines1.jpg, images/lez11pathlines2.jpg},
  thumbnails = {images/lez11pathlines1_thumb.jpg, images/lez11pathlines2_thumb.jpg},
  project = {semseg}    
}

@article{angelelli11ultrasoundStatistics,
  author = {Paolo Angelelli and Kim Nylund and Odd Helge Gilja and Helwig Hauser},
  title = {Interactive Visual Analysis of Contrast-enhanced Ultrasound Data
based on Small Neighborhood Statistics},
  year = {2011},
  abstract = {Contrast-enhanced ultrasound (CEUS) has recently become an important 
technology for lesion detection and characterization in cancer diagnosis. CEUS is 
used to investigate the perfusion kinetics in tissue over time, which relates to 
tissue vascularization. In this paper we present a pipeline that enables interactive 
visual exploration and semi-automatic segmentation and classification of CEUS data.

For the visual analysis of this challenging data, with characteristic noise patterns 
and residual movements, we propose a robust method to derive expressive enhancement 
measures from small spatio-temporal neighborhoods. We use this information in a staged
visual analysis pipeline that leads from a more local investigation to global results 
such as the delineation of anatomic regions according to their perfusion properties. 
To make the visual exploration interactive, we have developed an accelerated framework
based on the OpenCL library, that exploits modern many-cores hardware. Using our 
application, we were able to analyze datasets from CEUS liver examinations, being able 
to identify several focal liver lesions, segment and analyze them quickly and 
precisely, and eventually characterize them.},
  journal = {Computers \& Graphics - Special Issue on Visual Computing in Biology and Medicine},
  volume = {35},
  number = {2},
  pages = {218--226},
  URL = {http://dx.doi.org/10.1016/j.cag.2010.12.005},
  images = {images/angelelli11ultrasoundStatistics2.jpg, images/angelelli11ultrasoundStatistics1.jpg},
  thumbnails = {images/angelelli11ultrasoundStatistics2_thumb.jpg, images/angelelli11ultrasoundStatistics1_thumb.jpg},  
  project = {illustrasound,medviz,illvis},
  vid = {http://www.ii.uib.no/vis/publications/vids/angelelli11CEUSSegmentation.wmv},
  pdf = {pdfs/angelelli11CEUSIVA.pdf}
}

@inproceedings{lampe11kde,
  title = {Interactive Visualization of Streaming Data with Kernel Density Estimation},
  author = {Ove Daae Lampe and Helwig Hauser},
  year = {2011},
  booktitle = {Proceedings of the IEEE Pacific Visualization Symposium (PacificVis 2011)},
  abstract = {In this paper, we discuss the extension and integration 
of the statistical concept of Kernel Density Estimation (KDE) in a 
scatterplot-like visualization for dynamic data at interactive rates. 
We present a line kernel for representing streaming data, we discuss 
how the concept of KDE can be adapted to enable a continuous 
representation of the distribution of a dependent variable of a 
2D domain. We propose to automatically adapt the kernel bandwith of 
KDE to the viewport settings, in an interactive visualization 
environment that allows zooming and panning. We also present a 
GPU-based realization of KDE that leads to interactive frame rates, 
even for comparably large datasets. Finally, we demonstrate the 
usefulness of our approach in the context of three application 
scenarios -- one studying streaming ship traffic data, another one 
from the oil and gas domain, where process data from the operation 
of an oil rig is streaming in to an on-shore operational center, and 
a third one studying commercial air traffic in the US spanning 1987 to 2008.},
  pages = {171--178},
  month = {March},
  location = {Hong Kong},
  vid = {vids/lampe11kde.html},
  pdf = {pdfs/lampe11kde.pdf},
  URL = {http://dx.doi.org/10.1109/PACIFICVIS.2011.5742387},
  images = {images/lampe11kde1.jpg, images/lampe11kde2.jpg},
  thumbnails = {images/lampe11kde1_thumb.jpg, images/lampe11kde2_thumb.jpg},
}

@misc{viola11passingThrough,
  author = {Ivan Viola},
  title  ={Passing Through the Trough of Disillusionment of Illustrative Visualization},
  year = {2011},
  month = {September},
  howpublished = {Keynote at EG-UK Theory and Practice of Computer Graphics Conference (TP.CG.2011)},
  location = {Warwick, UK},
  abstract = {Efficient illustration craft is a vast source of 
inspiration for development of new visual abstractions in data 
visualization. Many new illustration-inspired techniques have 
emerged up to now, primarily arguing their validity with a 
statement like: "The illustrators have been using this technique 
for centuries and therefore we adapt their technique for interactive 
data display..." Argumentation of such kind was stimulating in the 
initial phase of illustrative visualization research, but nowadays 
this reasoning is no longer satisfactory. It is becoming apparent 
that ad-hoc adaptation can have arbitrary outcome. A systematic 
adaptation requires a vivid dialog with illustrators and a 
well-founded reasoning by means of the vision and cognitive 
sciences. This talk will assess the efficiency of selected 
visual abstractions, adapted for interactive visualization, in 
terms of their consistency with established perceptual principles.},
  pres = {pdfs/viola11passingThrough.pdf},
  vid = {https://picasaweb.google.com/viola.ivan/Talks#5651394119519056546},
  images = {images/viola11passingThrough.jpg},
  thumbnails = {images/viola11passingThrough_thumb.jpg},
}