EuroVis07: Joint Eurographics - IEEE VGTC Symposium on Visualization

Permanent URI for this collection

https://diglib7.eg.org/handle/10.2312/398

Relevance Driven Visualization of Financial Performance Measures

[meta data] [files:
019-026.pdf
]
Ziegler, Hartmut
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Nietzschmann, Tilo
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Keim, Daniel A.

Multiscale Visualization of Dynamic Software Logs

[meta data] [files:
011-018.pdf
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Moreta, Sergio
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Telea, Alexandru

Depth Cues and Density in Temporal Parallel Coordinates

[meta data] [files:
035-042.pdf
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Johansson, Jimmy
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Ljung, Patric
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Cooper, Matthew

KeyStrokes: Personalizing Typed Text with Visualization

[meta data] [files:
043-050.pdf
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Neumann, Petra
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Tat, Annie
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Zuk, Torre
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Carpendale, Sheelagh

Multi-Resolution Techniques for Visual Exploration of Large Time-Series Data

[meta data] [files:
027-034.pdf
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Hao, Ming
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Dayal, Umeshwar
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Keim, Daniel
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Schreck, Tobias

Visualization of Uncertainty in Lattices to Support Decision-Making

[meta data] [files:
051-058.pdf
]
Collins, Christopher
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Carpendale, Sheelagh
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Penn, Gerald

Manual Clustering Refinement using Interaction with Blobs

[meta data] [files:
059-066.pdf
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Heine, Christian
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Scheuermann, Gerik

Grouse: Feature-Based, Steerable Graph Hierarchy Exploration

[meta data] [files:
067-074.pdf ,
grousevid2.gz
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Archambault, Daniel
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Munzner, Tamara
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Auber, David

Story Telling for Presentation in Volume Visualization

[meta data] [files:
091-098.pdf
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Wohlfart, Michael
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Hauser, Helwig

Online Dynamic Graph Drawing

[meta data] [files:
075-082.pdf ,
DynamicGraphs.mov
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Frishman, Yaniv
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Tal, Ayellet

Path Visualization for Adjacency Matrices

[meta data] [files:
083-090.pdf
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Shen, Zeqian
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Ma, Kwan-Liu

Dimensional Congruence for Interactive Visual Data Mining and Knowledge Discovery

[meta data] [files:
099-106.pdf
]
Baumgaertner, Sebastian
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Ebert, Achim
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Deller, Matthias

TrustNeighborhoods: Visualizing Trust in Distributed File Sharing Systems

[meta data] [files:
107-114.pdf ,
trustvis-example.png ,
trustvis-mockup1.png ,
trustvis-mockup2.png
]
Elmqvist, Niklas
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Tsigas, Philippas

Interactive Visualization of Multi-Field Medical Data Using Linked Physical and Feature-Space Views

[meta data] [files:
123-130.pdf
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Blaas, Jorik
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Botha, Charl P.
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Post, Frits H.

A Tri-Space Visualization Interface for Analyzing Time-Varying Multivariate Volume Data

[meta data] [files:
115-122.pdf
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Akiba, Hiroshi
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Ma, Kwan-Liu

The CoMIRVA Toolkit for Visualizing Music-Related Data

[meta data] [files:
147-154.pdf
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Schedl, Markus
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Knees, Peter
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Seyerlehner, Klaus
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Pohle, Tim

Design of Multi-dimensional Transfer Functions Using Dimensional Reduction

[meta data] [files:
131-138.pdf ,
video.avi
]
Pinto, Francisco de Moura
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Freitas, Carla M. D. S.

Subdivision Volume Splatting

[meta data] [files:
139-146.pdf
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McDonnell, Kevin T.
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Neophytou, Neophytos
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Mueller, Klaus
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Qin, Hong

Sonar Explorer: A New Tool for Visualization of Fish Schools from 3D Sonar Data

[meta data] [files:
155-162.pdf
]
Balabanian, Jean-Paul
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Viola, Ivan
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Ona, Egil
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Patel, Ruben
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Groeller, Eduard

See What You Know: Analyzing Data Distribution to Improve Density Map Visualization

[meta data] [files:
163-170.pdf
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Bertini, Enrico
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Girolamo, Alessio Di
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Santucci, Giuseppe

Integrating Local Feature Detectors in the Interactive Visual Analysis of Flow Simulation Data

[meta data] [files:
171-178.pdf
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Buerger, Raphael
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Muigg, Philipp
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Ilcík, Martin
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Doleisch, Helmut
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Hauser, Helwig

Feature Identification and Extraction in Function Fields

[meta data] [files:
195-201.pdf
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Anderson, John C.
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Gosink, Luke J.
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Duchaineau, Mark A.
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Joy, Kenneth I.

Flexible And Topologically Localized Segmentation

[meta data] [files:
179-186.pdf
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Johansson, Gunnar
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Museth, Ken
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Carr, Hamish

Segmentation of DT-MRI Anisotropy Isosurfaces

[meta data] [files:
187-194.pdf
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Schultz, Thomas
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Theisel, Holger
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Seidel, Hans-Peter

Animation of Orthogonal Texture-Based Vector Field Visualization

[meta data] [files:
219-226.pdf
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Bachthaler, Sven
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Weiskopf, Daniel

Visualization Methods for Vortex Rings and Vortex Breakdown Bubbles

[meta data] [files:
211-218.pdf ,
draftTubeBubble.avi
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Peikert, Ronald
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Sadlo, Filip

Parametric Visualization of High Resolution Correlated Multi-spectral Features Using PCA

[meta data] [files:
203-210.pdf
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Broersen, Alexander
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Liere, Robert van
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Heeren, Ron M. A.

Functional Unit Maps for Data-Driven Visualization of High-Density EEG Coherence

[meta data] [files:
259-266.pdf
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Caat, Michael ten
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Maurits, Natasha M.
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Roerdink, Jos B. T. M.

Multiresolution MIP Rendering of Large Volumetric Data Accelerated on Graphics Hardware

[meta data] [files:
243-250.pdf
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Laan, Wladimir J. van der
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Jalba, Andrei C.
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Roerdink, Jos B. T. M.

Interactive Visual Exploration of Unsteady 3D Flows

[meta data] [files:
251-258.pdf
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Buerger, Kai
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Schneider, Jens
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Kondratieva, Polina
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Krueger, J.
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Westermann, Ruediger

Priority Streamlines: A context-based Visualization of Flow Fields

[meta data] [files:
227-234.pdf ,
animation.mpg
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Schlemmer, Michael
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Hotz, Ingrid
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Hamann, Bernd
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Morr, Florian
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Hagen, Hans

Hardware-accelerated Stippling of Surfaces derived from Medical Volume Data

[meta data] [files:
235-242.pdf
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Baer, Alexandra
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Tietjen, Christian
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Bade, Ragnar
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Preim, Bernhard

Viewpoint Selection for Intervention Planning

[meta data] [files:
267-274.pdf ,
Muehler_ViewpointSelectionForInterventionPlanning.avi
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Muehler, Konrad
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Neugebauer, Mathias
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Tietjen, Christian
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Preim, Bernhard

Model-free Surface Visualization of Vascular Trees

[meta data] [files:
283-290.pdf
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Schumann, Christian
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Oeltze, Steffen
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Bade, Ragnar
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Preim, Bernhard
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Peitgen, H.- O.

Feature Emphasis and Contextual Cutaways for Multimodal Medical Visualization

[meta data] [files:
275-282.pdf
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Burns, Michael
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Haidacher, Martin
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Wein, Wolfgang
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Viola, Ivan
; 
Groeller, Eduard

Browse

Recent Submissions

Now showing 1 - 35 of 35
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    Relevance Driven Visualization of Financial Performance Measures
    (The Eurographics Association, 2007) Ziegler, Hartmut; Nietzschmann, Tilo; Keim, Daniel A.; K. Museth and T. Moeller and A. Ynnerman
    Visual data analysis has received a lot of research interest in recent years, and a wide variety of new visualization techniques and applications have been developed to improve insight into the various application domains. In financial data analysis, however, analysts still primarily rely on a set of statistical performance parameters in combination with traditional line charts in order to evaluate assets and to make decisions, and information visualization is only very slowly entering this important domain. In this paper, we analyze some of the standard statistical measures for technical financial data analysis and demonstrate cases where they produce insufficient and misleading results that do not reflect the real performance of an asset. We propose a technique for visualizing financial time series data that eliminates these inadequacies, offering a complete view on the real performance of an asset. The technique is enhanced by relevance and weighting functions according to the users' preferences in order to emphasize specific regions of interest. Based on these principles we redefine some of the standard performance measures. We apply our technique on real world financial data sets and combine it with higher-level financial analysis techniques such as performance/risk analysis, dominance evaluation, and efficiency curves in order to show how traditional techniques from economics can be improved by modern visual data analysis techniques.
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    Multiscale Visualization of Dynamic Software Logs
    (The Eurographics Association, 2007) Moreta, Sergio; Telea, Alexandru; K. Museth and T. Moeller and A. Ynnerman
    We present a set of techniques and design principles for the visualization of large dynamic software logs consisting of attributed change events, such as obtained from instrumenting programs or mining software repositories. We enhance the visualization scalability with importance-based antialiasing techniques that guarantee visibility of several types of events. We present a hierarchical clustering method that uncovers several patterns of interest in the event logs, such as same-lifetime memory allocations and software releases. We visualize the clusters using a new type of technique called interleaved cushions. We demonstrate our methods on two real-world problems: the monitoring of a dynamic memory allocator and the analysis of a software repository.
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    Depth Cues and Density in Temporal Parallel Coordinates
    (The Eurographics Association, 2007) Johansson, Jimmy; Ljung, Patric; Cooper, Matthew; K. Museth and T. Moeller and A. Ynnerman
    This paper introduces Temporal Density Parallel Coordinates (TDPC) and Depth Cue Parallel Coordinates (DCPC) which extend the standard 2D parallel coordinates technique to capture time-varying dynamics. The proposed techniques can be used to analyse temporal positions of data items as well as temporal positions of changes occurring using 2D displays. To represent temporal changes, polygons (instead of traditional lines) are rendered in parallel coordinates. The results presented show that rendering polygons is superior at revealing large temporal changes. Both TDPC and DCPC have been efficiently implemented on the GPU allowing the visualization of thousands of data items over thousands of time steps at interactive frame rates.
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    KeyStrokes: Personalizing Typed Text with Visualization
    (The Eurographics Association, 2007) Neumann, Petra; Tat, Annie; Zuk, Torre; Carpendale, Sheelagh; K. Museth and T. Moeller and A. Ynnerman
    With the ubiquity of typed text, the style and much of the personality of handwriting has been lost from general communication. To counter this we introduce an artistic real-time visualization of typed messages that additionally captures and encodes aspects of an individual's unique typing style. The potential of our system to augment electronic communication was evaluated and the results are provided along with analysis of their implications for social visualization.
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    Multi-Resolution Techniques for Visual Exploration of Large Time-Series Data
    (The Eurographics Association, 2007) Hao, Ming; Dayal, Umeshwar; Keim, Daniel; Schreck, Tobias; K. Museth and T. Moeller and A. Ynnerman
    Time series are a data type of utmost importance in many domains such as business management and service monitoring. We address the problem of visualizing large time-related data sets which are difficult to visualize effectively with standard techniques given the limitations of current display devices. We propose a framework for intelligent time- and data-dependent visual aggregation of data along multiple resolution levels. This idea leads to effective visualization support for long time-series data providing both focus and context. The basic idea of the technique is that either data-dependent or application-dependent, display space is allocated in proportion to the degree of interest of data subintervals, thereby (a) guiding the user in perceiving important information, and (b) freeing required display space to visualize all the data. The automatic part of the framework can accommodate any time series analysis algorithm yielding a numeric degree of interest scale. We apply our techniques on real-world data sets, compare it with the standard visualization approach, and conclude the usefulness and scalability of the approach.
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    Visualization of Uncertainty in Lattices to Support Decision-Making
    (The Eurographics Association, 2007) Collins, Christopher; Carpendale, Sheelagh; Penn, Gerald; K. Museth and T. Moeller and A. Ynnerman
    Lattice graphs are used as underlying data structures in many statistical processing systems, including natural language processing. Lattices compactly represent multiple possible outputs and are usually hidden from users. We present a novel visualization intended to reveal the uncertainty and variability inherent in statistically-derived lattice structures. Applications such as machine translation and automated speech recognition typically present users with a best-guess about the appropriate output, with apparent complete confidence. Through case studies we show how our visualization uses a hybrid layout along with varying transparency, colour, and size to reveal the lattice structure, expose the inherent uncertainty in statistical processing, and help users make better-informed decisions about statistically-derived outputs.
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    Manual Clustering Refinement using Interaction with Blobs
    (The Eurographics Association, 2007) Heine, Christian; Scheuermann, Gerik; K. Museth and T. Moeller and A. Ynnerman
    The huge amount of different automatic clustering methods emphasizes one thing: there is no optimal clustering method for all possible cases. In certain application domains, like genomics and natural language processing, it is not even clear if any of the already known clustering methods suffice. In such cases, an automatic clustering method is often followed by manual refinement. The refined version may then be used as either an illustration, a reference, or even an input for a rule based or other machine learning algorithm as a new clustering method. In this paper, we describe a novel interaction technique to manual cluster refinement using the metaphor of soap bubbles, represented by special implicit surfaces (blobs). For instance, entities can simply be moved inside and outside of these blobs. A modified force-directed layout process automatically arranges entities equidistant on the screen. The modifications include a reduction to the expected amount of computation per iteration down to O(|V| log |V|+|E|) in order to achieve a high response time for use in an interactive system. We also spend a considerable amount of effort making the display of blobs fast enough for an interactive system.
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    Grouse: Feature-Based, Steerable Graph Hierarchy Exploration
    (The Eurographics Association, 2007) Archambault, Daniel; Munzner, Tamara; Auber, David; K. Museth and T. Moeller and A. Ynnerman
    Grouse is a feature-based approach to steerable exploration of a graph and an associated hierarchy. Steerability allows exploration to begin immediately, rather than requiring a costly layout of the entire graph as an initial step. In a feature-based approach, the subgraph inside a metanode of the graph hierarchy is laid out with a well- chosen algorithm appropriate for its topological structure. Grouse preserves the input hierarchy, which provides meaningful information to the user when its metanodes correspond to features of interest. When a metanode in the hierarchy is opened, a limited number of metanodes are laid out again along the path between the opened node and the root. We demonstrate the effectiveness of Grouse on datasets from IMDB, the Internet Movie Database, where nodes are actors and cliques represent movies. The combination of feature-based layout and limited relayout computation does not fragment features in the hierarchy and improves the number of levels in the hierarchy that can be seen at once over previous approaches.
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    Story Telling for Presentation in Volume Visualization
    (The Eurographics Association, 2007) Wohlfart, Michael; Hauser, Helwig; K. Museth and T. Moeller and A. Ynnerman
    In this paper we present a novel approach to volume visualization for presentation purposes that improves both the comprehensibility and credibility of the intended visualization message. Therefore, we combine selected aspects from storytelling as well as from interactive volume visualization to create a guided but at the same time interactive visualization presentation approach. To ease the observer's access to a presented visualization result we not only communicate the result itself, but also deliver its creational process in the form of an annotated visualization animation, which we call a visualization story. Additionally, we enable variable means of interactivity during story playback. The story observers may just watch the presentation passively, but they are also allowed to reinvestigate the visualization independently from story guidance, offering the ability to verify, confirm, or even disapprove the presented visualization message. For demonstration purposes, we developed a prototype application that provides tools to author, edit, and watch visualization stories. We demonstrate the potential of our approach on the basis of medical visualization examples.
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    Online Dynamic Graph Drawing
    (The Eurographics Association, 2007) Frishman, Yaniv; Tal, Ayellet; K. Museth and T. Moeller and A. Ynnerman
    This paper presents an algorithm for drawing a sequence of graphs online. The algorithm strives to maintain the global structure of the graph and thus the user's mental map, while allowing arbitrary modifications between consecutive layouts. The algorithm works online and uses various execution culling methods in order to reduce the layout time and handle large dynamic graphs. Techniques for representing graphs on the GPU allow a speedup by a factor of up to 8 compared to the CPU implementation. An application to visualization of discussion threads in Internet sites is provided.
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    Path Visualization for Adjacency Matrices
    (The Eurographics Association, 2007) Shen, Zeqian; Ma, Kwan-Liu; K. Museth and T. Moeller and A. Ynnerman
    For displaying a dense graph, an adjacency matrix is superior than a node-link diagram because it is more compact and free of visual clutter. A node-link diagram, however, is far better for the task of path finding because a path can be easily traced by following the corresponding links, provided that the links are not heavily crossed or tangled.We augment adjacency matrices with path visualization and associated interaction techniques to facilitate path finding. Our design is visually pleasing, and also effectively displays multiple paths based on the design commonly found in metro maps. We illustrate and assess the key aspects of our design with the results obtained from two case studies and an informal user study.
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    Dimensional Congruence for Interactive Visual Data Mining and Knowledge Discovery
    (The Eurographics Association, 2007) Baumgaertner, Sebastian; Ebert, Achim; Deller, Matthias; K. Museth and T. Moeller and A. Ynnerman
    Many authors in the field of 3D human computer interaction have described the advantages of 3D user interfaces: Intuitive metaphors from daily life, immersive workspaces, virtual environments that closely resemble natural environments, and the usefulness of the third dimension as an additional visualization scale. Nevertheless, there are still few or no successful applications for complex information spaces that make use of it in a natural human-centered manner. In this paper, we propose a novel hybrid user interface for knowledge workers to support document spaces and corresponding visualizations. We propose a combined 2D + 3D interface to support both visualization approaches and interaction metaphors to their maximum potential. Interaction is matched due to the principle of dimensional congruence and a thorough investigation of previous approaches and problems is given. Finally, a user study to evaluate the effectiveness and usability of the proposed system is presented.
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    TrustNeighborhoods: Visualizing Trust in Distributed File Sharing Systems
    (The Eurographics Association, 2007) Elmqvist, Niklas; Tsigas, Philippas; K. Museth and T. Moeller and A. Ynnerman
    We present TrustNeighborhoods, a security trust visualization for situational awareness on the Internet aimed at novice and intermediate users of a distributed file sharing system. The TrustNeighborhoods technique uses the metaphor of a multi-layered city or fortress to intuitively represent trust as a simple geographic relation. The visualization uses a radial space-filling layout; there is a 2D mode for editing and configuration, as well as a 3D mode for exploration and overview. In addition, the 3D mode supports a simple animated "fly-to" command that is intended to show the user the context and trust of a particular document by zooming in on the document and its immediate neighborhood in the 3D city. The visualization is intended for integration into an existing desktop environment, connecting to the distributed file sharing mechanisms of the environment and non-obtrusively displaying a 3D orientation animation in the background for any file being accessed over the network. A formal user study shows that the technique supports significantly higher trust assignment accuracy than manual trust assignment at the cost of only a minor time investment.
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    Interactive Visualization of Multi-Field Medical Data Using Linked Physical and Feature-Space Views
    (The Eurographics Association, 2007) Blaas, Jorik; Botha, Charl P.; Post, Frits H.; K. Museth and T. Moeller and A. Ynnerman
    Multi-field datasets contain multiple parameters defined over the same spatio-temporal domain. In medicine, such multi-field data is being used more often every day, and there is an urgent need for exploratory visualization approaches that are able to deal effectively with the data-analysis. In this paper, we present a highly interactive, coordinated view-based visualization approach that has been developed especially for dealing with multi-field medical data. It can show any number of views of the physical domain and also of the abstract high-dimensional feature space. The approach has been optimized for interactive use with very large datasets. It is based on intuitive interaction techniques, and integrates analysis techniques from pattern classification to guide the exploration process. We will give some details about the implementation, and we demonstrate the utility of our approach with two real medical use cases.
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    A Tri-Space Visualization Interface for Analyzing Time-Varying Multivariate Volume Data
    (The Eurographics Association, 2007) Akiba, Hiroshi; Ma, Kwan-Liu; K. Museth and T. Moeller and A. Ynnerman
    The dataset generated by a large-scale numerical simulation may include thousands of timesteps and hundreds of variables describing different aspects of the modeled physical phenomena. In order to analyze and understand such data, scientists need the capability to explore simultaneously in the temporal, spatial, and variable domains of the data. Such capability, however, is not generally provided by conventional visualization tools. This paper presents a new visualization interface addressing this problem. The interface consists of three components which abstracts the complexity of exploring in temporal, variable, and spatial domain, respectively. The first component displays time histograms of the data, helps the user identify timesteps of interest, and also helps specify time-varying features. The second component displays correlations between variables in parallel coordinates and enables the user to verify those correlations and possibly identity unanticipated ones. The third component allows the user to more closely explore and validate the data in spatial domain while rendering multiple variables into a single visualization in a user controllable fashion. Each of these three components is not only an interface but is also the visualization itself, thus enabling efficient screen-space usage. The three components are tightly linked to facilitate tri-space data exploration, which offers scientists new power to study their time-varying, multivariate volume data.
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    The CoMIRVA Toolkit for Visualizing Music-Related Data
    (The Eurographics Association, 2007) Schedl, Markus; Knees, Peter; Seyerlehner, Klaus; Pohle, Tim; K. Museth and T. Moeller and A. Ynnerman
    We present CoMIRVA, which is an abbreviation for Collection of Music Information Retrieval and Visualization Applications. CoMIRVA is a Java framework and toolkit for information retrieval and visualization. It is licensed under the GNU GPL and can be downloaded from http://www.cp.jku.at/comirva/. At the moment, the main functionalities include music information retrieval, web retrieval, and visualization of the extracted information. In this paper, we focus on the visualization aspects of CoMIRVA. Since many of the information retrieval functions are intended to be applied to problems of the field of music information retrieval (MIR), we demonstrate the functions using data like similarity matrices of music artists gained by analyzing artist-related web pages. CoMIRVA is continuously being extended. Currently, it supports the following visualization techniques: Self-Organizing Map, Smoothed Data Histogram, Circled Bars, Circled Fans, Probabilistic Network, Continuous Similarity Ring, Sunburst, and Music Description Map. Since space is limited, we can only present a selected number of these in this paper. As one key feature of CoMIRVA is its easy extensibility, we further elaborate on how CoMIRVA was used for creating a novel user interface to digital music repositories.
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    Design of Multi-dimensional Transfer Functions Using Dimensional Reduction
    (The Eurographics Association, 2007) Pinto, Francisco de Moura; Freitas, Carla M. D. S.; K. Museth and T. Moeller and A. Ynnerman
    Direct volume rendering techniques allow visualization of volume data without extracting intermediate geometry. The mapping from voxel attributes to optical properties is performed by transfer functions which, consequently, play a crucial role in building informative images from the data. One-dimensional transfer functions, which are based only on a scalar value per voxel, often do not provide proper visualizations. On the other hand, multidimensional transfer functions can perform more sophisticated data classification, based on vectorial voxel signatures. The transfer function design is a non-trivial and unintuitive task, especially in the multi-dimensional case. In this paper we propose a multi-dimensional transfer function design technique that uses self-organizing maps to perform dimensional reduction. Our approach gives uniform treatment to volume data containing voxel signatures of arbitrary dimension, and allows the use of any type of voxel attribute as part of the voxel signatures.
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    Subdivision Volume Splatting
    (The Eurographics Association, 2007) McDonnell, Kevin T.; Neophytou, Neophytos; Mueller, Klaus; Qin, Hong; K. Museth and T. Moeller and A. Ynnerman
    Volumetric Subdivision (VS) is a powerful paradigm that enables volumetric sculpting and realistic volume deformations that give rise to the concept of "virtual clay". In VS, volumes are commonly represented as a space-filling set of deformed polyhedra, which can be further decomposed into a mesh of tetrahedra for rendering. Images can then be generated via tetrahedral projection or raycasting. A current shortcoming in VS-based operations is the need for a very high level of subdivision to represent fine detail in the mesh and to obtain a high-fidelity visualization. However, we have discovered that the subdivision process itself can be closely simulated with radial basis functions (RBFs), making it possible to replace the finer subdivision levels by a coarser aggregation of RBF kernels. This reduction to a simplified assembly of RBFs subsequently enables interactive rendering of volumetric subdivision shapes within a GPU-based volume splatting framework.
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    Sonar Explorer: A New Tool for Visualization of Fish Schools from 3D Sonar Data
    (The Eurographics Association, 2007) Balabanian, Jean-Paul; Viola, Ivan; Ona, Egil; Patel, Ruben; Groeller, Eduard; K. Museth and T. Moeller and A. Ynnerman
    We present a novel framework for analysis and visualization of fish schools in 3D sonar surveys. The 3D sonar technology is new and there have not been applications to visualize the data in 3D. We have created an application called Sonar Explorer that satisfies the requirements of domain scientists. Sonar Explorer provides easy and intuitive semi-automatic fish school tracking and survey map generation. The overall pipeline is described and all pipeline stages relevant for visualization are highlighted. We present techniques to deal with 3D sonar data specifics: highly anisotropic volume data aligned on a curvilinear grid. Domain scientists provide initial impressions on interaction and outlook.
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    See What You Know: Analyzing Data Distribution to Improve Density Map Visualization
    (The Eurographics Association, 2007) Bertini, Enrico; Girolamo, Alessio Di; Santucci, Giuseppe; K. Museth and T. Moeller and A. Ynnerman
    Density maps allow for visually rendering density differences, usually mapping density values to a grey or color scale. The paper analyzes the drawbacks arising from the commonly used strategies and introduces a novel technique able to improve the overall mapping process. The technique is driven by statistical knowledge about the density distribution and a set of quality metrics allows for validating, in an objective way, its effectiveness.
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    Integrating Local Feature Detectors in the Interactive Visual Analysis of Flow Simulation Data
    (The Eurographics Association, 2007) Buerger, Raphael; Muigg, Philipp; Ilcík, Martin; Doleisch, Helmut; Hauser, Helwig; K. Museth and T. Moeller and A. Ynnerman
    We present smooth formulations of common vortex detectors that allow a seamless integration into the concept of interactive visual analysis of flow simulation data. We express the originally binary feature detectors as fuzzy-sets that can be combined using the linking and brushing concepts of interactive visual analysis. Both interaction and visualization gain from having multiple detectors concurrently available and from the ability to combine them. An application study on automotive data reveals how these vortex detectors combine and perform in praxis.
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    Feature Identification and Extraction in Function Fields
    (The Eurographics Association, 2007) Anderson, John C.; Gosink, Luke J.; Duchaineau, Mark A.; Joy, Kenneth I.; K. Museth and T. Moeller and A. Ynnerman
    We present interactive techniques for identifying and extracting features in function fields. Function fields map points in n-dimensional Euclidean space to 1-dimensional scalar functions. Visual feature identification is ac- complished by interactively rendering scalar distance fields, constructed by applying a function-space distance metric over the function field. Combining visual exploration with feature extraction queries, formulated as a set of function-space constraints, facilitates quantitative analysis and annotation. Numerous application domains give rise to function fields. We present results for two-dimensional hyperspectral images, and a simulated time-varying, three-dimensional air quality dataset.
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    Flexible And Topologically Localized Segmentation
    (The Eurographics Association, 2007) Johansson, Gunnar; Museth, Ken; Carr, Hamish; K. Museth and T. Moeller and A. Ynnerman
    One of the most common visualization tasks is the extraction of significant boundaries, often performed with isosurfaces or level set segmentation. Isosurface extraction is simple and can be guided by geometric and topological analysis, yet frequently does not extract the desired boundary. Level set segmentation is better at boundary extraction, but either leads to global segmentation without edges, [CV01], that scales unfavorably in 3D or requires an initial estimate of the boundary from which to locally solve segmentation with edges. We propose a hybrid system in which topological analysis is used for semi-automatic initialization of a level set segmentation, and geometric information bounded topologically is used to guide and accelerate an iterative segmentation algorithm that combines several state-of-the-art level set terms. We thus combine and improve both the flexible isosurface interface and level set segmentation without edges.
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    Segmentation of DT-MRI Anisotropy Isosurfaces
    (The Eurographics Association, 2007) Schultz, Thomas; Theisel, Holger; Seidel, Hans-Peter; K. Museth and T. Moeller and A. Ynnerman
    While isosurfaces of anisotropy measures for data from diffusion tensor magnetic resonance imaging (DT-MRI) are known to depict major anatomical structures, the anisotropy metric reduces the rich tensor data to a simple scalar field. In this work, we suggest that the part of the data which has been ignored by the metric can be used to segment anisotropy isosurfaces into anatomically meaningful regions. For the implementation, we propose an edge-based watershed method that adapts and extends a method from curvature-based mesh segmentation [MW99]. Finally, we use the segmentation results to enhance visualization of the data.
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    Animation of Orthogonal Texture-Based Vector Field Visualization
    (The Eurographics Association, 2007) Bachthaler, Sven; Weiskopf, Daniel; K. Museth and T. Moeller and A. Ynnerman
    This paper introduces orthogonal vector field visualization on 2D manifolds: a representation by lines that are perpendicular to the input vector field. Line patterns are generated by line integral convolution (LIC). This visualization is combined with animation based on motion along the vector field. This decoupling of the line direction from the direction of animation allows us to choose the spatial frequencies along the direction of motion independently from the length scales along the LIC line patterns. Vision research indicates that local motion detectors are tuned to certain spatial frequencies of textures, and the above decoupling enables us to generate spatial frequencies optimized for motion perception. In addition, a filtering process is described to achieve a consistent and temporally coherent animation of the orthogonal vector field visualization. We present respective visualization algorithms for 2D planar vector fields and tangential vector fields on curved surfaces, and demonstrate that those algorithms lend themselves to efficient and interactive GPU implementations.
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    Visualization Methods for Vortex Rings and Vortex Breakdown Bubbles
    (The Eurographics Association, 2007) Peikert, Ronald; Sadlo, Filip; K. Museth and T. Moeller and A. Ynnerman
    Vortex breakdown bubbles are a subject which is of interest in many disciplines such as aeronautics, mixing, and combustion. Existing visualization methods are based on stream surfaces, direct volume rendering, tensor field visualization, and vector field topology. This paper presents a topological approach which is more closely oriented at the underlying theory of continuous dynamical systems. Algorithms are described for the detection of vortex rings and vortex breakdown bubbles, and for visualization of their characteristic properties such as the boundary, the chaotic dynamics, and possible islands of stability. Since some of these require very long streamlines, the effect of numerically introduced divergence has to be considered. From an existing subdivision scheme, a novel method for divergence conserving interpolation of cuboid cells is derived, and results are compared with those from standard trilinear interpolation. Also a comparison of results obtained with and without divergence cleaning is given.
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    Parametric Visualization of High Resolution Correlated Multi-spectral Features Using PCA
    (The Eurographics Association, 2007) Broersen, Alexander; Liere, Robert van; Heeren, Ron M. A.; K. Museth and T. Moeller and A. Ynnerman
    An imaging mass spectrometer is an analytical instrument that can determine the spatial distribution of chemical compounds on complex surfaces. The output of the device is a multi-spectral datacube; a three-dimensional (3D) dataset in which the xy-dimension represents the surface position and the z-dimension represents the mass spectral distribution. Analysts try to discover correlations in spectral profiles and spatial distributions inside a datacube. New technological developments allow mass spectrometric imaging on a higher spatial and spectral resolution. In this paper we present a parametric visualization technique which allows an analyst to examine spectral and spatially correlated patterns on the highest possible resolution. Principal component analysis (PCA) is used to decompose the datacube into several discriminating components. We represent these extracted features as abstract geometric shapes and use three parameters to allow for data exploration. The first parameter thresholds the spectral contribution at which an extracted component is visualized. The level of detail the shapes is controlled by a second parameter and a third parameter determines at which density-level the extracted feature is represented. This new visualization technique enables an analyst to select the most relevant spectral correlations and investigate their specific spatial distribution. With this method, less noise is included in the visualization of extracted features and by introducing various levels of detail the full spectral resolution can be utilized.
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    Functional Unit Maps for Data-Driven Visualization of High-Density EEG Coherence
    (The Eurographics Association, 2007) Caat, Michael ten; Maurits, Natasha M.; Roerdink, Jos B. T. M.; K. Museth and T. Moeller and A. Ynnerman
    Synchronous electrical activity in different brain regions is generally assumed to imply functional relationships between these regions. A measure for this synchrony is electroencephalography (EEG) coherence, computed between pairs of signals as a function of frequency. Existing high-density EEG coherence visualizations are generally either hypothesis-driven, or data-driven graph visualizations which are cluttered. In this paper, a new method is presented for data-driven visualization of high-density EEG coherence, which strongly reduces clutter and is referred to as functional unit (FU) map. Starting from an initial graph, with vertices representing electrodes and edges representing significant coherences between electrode signals, we define an FU as a set of electrodes represented by a clique consisting of spatially connected vertices. In an FU map, the spatial relationship between electrodes is preserved, and all electrodes in one FU are assigned an identical gray value. Adjacent FUs are visualized with different gray values and FUs are connected by a line if the average coherence between FUs exceeds a threshold. Results obtained with our visualization are in accordance with known electrophysiological findings. FU maps can be used as a preprocessing step for conventional analysis.
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    Multiresolution MIP Rendering of Large Volumetric Data Accelerated on Graphics Hardware
    (The Eurographics Association, 2007) Laan, Wladimir J. van der; Jalba, Andrei C.; Roerdink, Jos B. T. M.; K. Museth and T. Moeller and A. Ynnerman
    This paper is concerned with a multiresolution representation for maximum intensity projection (MIP) volume rendering based on morphological pyramids which allows progressive refinement. We consider two algorithms for progressive rendering from the morphological pyramid: one which projects detail coefficients level by level, and a second one, called streaming MIP, which resorts the detail coefficients of all levels simultaneously with respect to decreasing magnitude of a suitable error measure. The latter method outperforms the level-by-level method, both with respect to image quality with a fixed amount of detail data, and in terms of flexibility of controlling approximation error or computation time. We improve the streaming MIP algorithm, present a GPU implementation for both methods, and perform a comparison with existing CPU and GPU implementations.
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    Interactive Visual Exploration of Unsteady 3D Flows
    (The Eurographics Association, 2007) Buerger, Kai; Schneider, Jens; Kondratieva, Polina; Krueger, J.; Westermann, Ruediger; K. Museth and T. Moeller and A. Ynnerman
    In this paper we present GPU-based techniques for the interactive visualization of large unsteady 3D flow fields on uniform grids. We propose a novel dual-core approach to asynchronously stream such fields from the CPU, thus enabling the efficient exploration of large time-resolved sequences. This approach decouples visualization from data handling, resulting in interactive frame rates. Built upon a previously published GPU particle engine for flow visualization we have developed new strategies to compute and to visualize path lines and streak lines on the GPU. To provide additional visual cues, focus+context techniques for polygonal meshes have been integrated. The proposed techniques are used in the visual analysis of the Terashake 2.1 earthquake simulation data, and they have been shown to be very effective in revealing the relevant information in this data.
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    Priority Streamlines: A context-based Visualization of Flow Fields
    (The Eurographics Association, 2007) Schlemmer, Michael; Hotz, Ingrid; Hamann, Bernd; Morr, Florian; Hagen, Hans; K. Museth and T. Moeller and A. Ynnerman
    Flow vector fields contain a wealth of information that needs to be visualized. As an extension of the well-known streamline technique, we have developed a context-based method for visualizing steady flow vector fields in two and three dimensions. We call our method "Priority Streamlines". In our approach, the density of the streamlines is controlled by a scalar function that can be user-defined, or be given by additional information (e.g., temperature, pressure, vorticity, velocity) considering the underlying flow vector field. In regions, which are interesting the streamlines are drawn with increased density, while less interesting regions are drawn sparsely. Since streamlines in the most important regions are drawn first, we can use thresholding to obtain a streamline representation highlighting essential features. Color-mapping and transparency can be used for visualizing other information hidden in the flow vector field.
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    Hardware-accelerated Stippling of Surfaces derived from Medical Volume Data
    (The Eurographics Association, 2007) Baer, Alexandra; Tietjen, Christian; Bade, Ragnar; Preim, Bernhard; K. Museth and T. Moeller and A. Ynnerman
    We present a fast hardware-accelerated stippling method which does not require any preprocessing for placing points on surfaces. The surfaces are automatically parameterized in order to apply stippling textures without major distortions. The mapping process is guided by a decomposition of the space in cubes. Seamless scaling with a constant density of points is realized by subdividing and summarizing cubes. Our mip-map technique enables arbitrarily scaling with one texture. Different shading tones and scales are facilitated by adhering to the constraints of tonal art maps. With our stippling technique, it is feasible to encode all scaling and brightness levels within one self-similar texture. Our method is applied to surfaces extracted from (segmented) medical volume data. The speed of the stippling process enables stippling for several complex objects simultaneously. We consider application scenarios in intervention planning (neck and liver surgery planning). In these scenarios, object recognition (shape perception) is supported by adding stippling to semi-transparently shaded objects which are displayed as context information.
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    Viewpoint Selection for Intervention Planning
    (The Eurographics Association, 2007) Muehler, Konrad; Neugebauer, Mathias; Tietjen, Christian; Preim, Bernhard; K. Museth and T. Moeller and A. Ynnerman
    Viewpoint selection is crucial for medical intervention planning. The interactive exploration of a scene with 3d objects involves the systematic analysis of several anatomic structures. Viewpoint selection techniques enhance the display of the currently selected structure. For animations in collaborative intervention planning and surgical education, the authoring process may be significantly enhanced if good' viewpoints for important objects as well as for the whole scene are chosen automatically.We describe a viewpoint selection technique guided by parameters like size of unoccluded surface, importance of occluding objects, preferred region and viewpoint stability. The influence of these parameters may be flexibly adjusted by weights. Parameter maps indicate the influence of the current parameter settings on the viewpoints. For selected applications, the weights may be predefined and reused for other cases. We also describe an informal user study which was accomplished to understand if our viewpoint selection strategies produce adequate results from the users' point of view.
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    Model-free Surface Visualization of Vascular Trees
    (The Eurographics Association, 2007) Schumann, Christian; Oeltze, Steffen; Bade, Ragnar; Preim, Bernhard; Peitgen, H.- O.; K. Museth and T. Moeller and A. Ynnerman
    Expressive and efficient visualizations of complex vascular structures are essential for medical applications, such as diagnosis and therapy planning. A variety of techniques has been developed which provide smooth high-quality visualizations of vascular structures based on rather simple model assumptions. For diagnostic applications, these model assumptions and the resulting deviations from the actual vessel surface are not acceptable. We present a model-free approach which employs the binary result of a prior vessel segmentation as input. Instead of directly converting the segmentation result into a surface, we compute a point cloud which is adaptively refined at thin structures, where aliasing effects are particularly obvious and artifacts may occur. The point cloud is transformed into a surface representation by means of MPU Implicits, which provide a smooth piecewise quadratic approximation. Our method has been applied to a variety of datasets including pathologic cases. The generated visualizations are considerably more accurate than model-based approaches. Compared to other model-free approaches, our method produces smoother results.
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    Feature Emphasis and Contextual Cutaways for Multimodal Medical Visualization
    (The Eurographics Association, 2007) Burns, Michael; Haidacher, Martin; Wein, Wolfgang; Viola, Ivan; Groeller, Eduard; K. Museth and T. Moeller and A. Ynnerman
    Dense clinical data like 3D Computed Tomography (CT) scans can be visualized together with real-time imaging for a number of medical intervention applications. However, it is difficult to provide a fused visualization that allows sufficient spatial perception of the anatomy of interest, as derived from the rich pre-operative scan, while not occluding the real-time image displayed embedded within the volume. We propose an importance-driven approach that presents the embedded data such that it is clearly visible along with its spatial relation to the surrounding volumetric material. To support this, we present and integrate novel techniques for importance specification, feature emphasis, and contextual cutaway generation. We show results in a clinical context where a pre-operative CT scan is visualized alongside a tracked ultrasound image, such that the important vasculature is depicted between the viewpoint and the ultrasound image, while a more opaque representation of the anatomy is exposed in the surrounding area.