EuroVisPosters

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Accurate and Memory-Efficient GPU Ray-Casting Algorithm for Volume Rendering Unstructured Grid Data
(The Eurographics Association, 2019) Gu, Gibeom; Kim, Duksu; Madeiras Pereira, João and Raidou, Renata Georgia
We present a novel GPU ray-casting algorithm for volume rendering unstructured grid data. We employ the per-pixel intersection list to guarantee accurate results for non-convex meshes. For efficient memory access for the lists on the GPU, we represent the intersection lists for all faces as an array. To increase ray-coherency in a thread block and improve memory access efficiency, we propose an image-tile based ray distribution method. Also, we found that a prior approach using a per-thread local buffer to reduce redundant computation is not proper for recent GPUs. Instead, we use an on-demand calculation strategy that achieves much better performance even when it allows duplicate computation. With a GPU, our method achieved up to 36.5 times higher performance for the ray-casting process, and 18.1 times higher performance for the entire volume rendering, compared with the Bunyk algorithm using a CPU core. Also, our approach showed up to 8.2 times higher performance than a GPU-based cell projection method while generating more accurate rendering results.
Accurate Molecular Atom Selection in VR
(The Eurographics Association, 2022) Molina, Elena; Vázquez, Pere-Pau; Krone, Michael; Lenti, Simone; Schmidt, Johanna
Accurate selection in cluttered scenes is complex because a high amount of precision is required. In Virtual Reality Environments, it is even worse, because it is more difficult for us to point a small object with our arms in the air. Not only our arms move slightly, but the button/trigger press reduces our weak stability. In this paper, we present two alternatives to the classical ray pointing intended to facilitate the selection of atoms in molecular environments. We have implemented and analyzed such techniques through an informal user study and found that they were highly appreciated by the users. This selection method could be interesting in other crowded environments beyond molecular visualization.
Accurate Visualization of Galaxy Velocity Fields from Three-Dimensional Integral Field Spectroscopy Data
(The Eurographics Association, 2020) Uchiki, Rikuo; Boussejra, Malik Olivier; Zhu, Liyu; Takeshima, Yuriko; Matsubayashi, Kazuya; Uemura, Makoto; Fujishiro, Issei; Byška, Jan and Jänicke, Stefan
In recent years, integral field spectroscopy (IFS) has become a major methodology in observational astronomy. Visual analysis of galactic motions is expected to play a crucial role in discovering the physical properties of galaxies. This poster presents a novel method for visualizing galaxy-specific motions using an emerging visual programming environment, Advanced Framework for Learning Astrophysical Knowledge (aflak), for visual analysis of three-dimensional IFS data. We demonstrate that the line-of-sight velocity of each region of galaxies can be more accurately visualized by coupling two specific kinds of aflak macros for generating position-velocity diagrams and deriving velocity fields.
ANARI: ANAlytic Rendering Interface
(The Eurographics Association, 2022) Griffin, Kevin; Amstutz, Jefferson; DeMarle, Dave; Günther, Johannes; Progsch, Jakob; Sherman, William; Stone, John E.; Usher, Will; Kooten, Kees van; Krone, Michael; Lenti, Simone; Schmidt, Johanna
The ANARI API enables users to build the description of a scene to generate imagery, rather than specifying the details of the rendering process, providing simplified visualization application development and cross-vendor portability to diverse rendering engines, including those using state-of-the-art ray tracing.
Automatic Segmentation of Tooth Images: Optimization of Multi-parameter Image Processing Workflow
(The Eurographics Association, 2022) Bressan Fogalli, Giovani; Line, Sérgio Roberto Peres; Baum, Daniel; Krone, Michael; Lenti, Simone; Schmidt, Johanna
The development of specific algorithms in image processing are usually related to dataset characteristics. Those characteristics will influence the number of instructions required to solve a problem. Normally, the more complex a set of instructions is, the more parameters need to be set. Dealing with such degrees of freedom, sometimes leading to subjective decision making, is time-consuming and frequently leads to errors or sub-optimal results of the developed model. Here, we deal with a model for segmentation of masks of tooth images containing a pattern of bands called Hunter-Schreger Bands (HSB). They appear on tooth surface when lit from the side. This segmentation process is only one step of a pipeline whose overall goal is human biometric identification to be used, e.g., in forensics. The segmentation algorithm, which exploits the anisotropy of the image, uses several parameters and choosing the optimal combination of them is challenging. The aim of this work was to utilize visual data analysis tools to optimize the chosen parameters and to understand their influence on the performance of the algorithm. Our results reveal that a slightly better combination of parameter values can be found starting from the experimentally determined initial parameters. This approach can be repeatedly performed to achieve even better parameterizations. To more deeply understand the influence of the parameters on the final result, more sophisticated visual interaction tools will be explored in future work.
BitConduite: Visualizing and Analyzing Activity on the Bitcoin Network
(The Eurographics Association, 2017) Kinkeldey, Christoph; Fekete, Jean-Daniel; Isenberg, Petra; Anna Puig Puig and Tobias Isenberg
BitConduite is a system we are developing for the visual exploration of financial activity on the Bitcoin network. Bitcoin is the largest digital pseudo-currency worldwide and its study is of increasing interest and importance to economists, bankers, policymakers, and law enforcement authorities. All financial transactions in Bitcoin are available in an openly accessible online ledger-the (Bitcoin) blockchain. Yet, the open data does not lend itself easily to an analysis of how different individuals and institutions-or entities on the network-actually use Bitcoin. Our system BitConduite offers a data transformation back end that gives us an entity-based access to the blockchain data and a visualization front end that supports a novel high-level view on transactions over time. In particular, it facilitates the exploration of activity through filtering and clustering interactions. We are developing our system with experts in economics and will conduct a formal user study to assess our approach of Bitcoin activity analysis.
Case Studies of Shareable Personal Map Visualization
(The Eurographics Association, 2018) Ruchikachorn, Puripant; Anna Puig and Renata Raidou
This paper presents two examples of personal data visualizations to be shared among peers. The visualized and shared data were travel destinations in Thailand and daily commutes in Bangkok, Thailand. The former gathered much attention with almost a million visitors within the first week after launch or approximately 2% of internet users in Thailand. Despite minimal data collection, large data samples of the first case study enable various analyses. The easy-to-use interfaces and simple visualizations can be a model of the genre of personal visualization whose main task is to share.
A Case Study on Implementing Screen Reader Accessibility in Dynamic Visualizations
(The Eurographics Association, 2022) Costa, Rita; Malveiro, Beatriz; Palmeiro, João; Bizarro, Pedro; Krone, Michael; Lenti, Simone; Schmidt, Johanna
Millions of people worldwide work in jobs where assessing dynamic data presented visually to them is a key part of their tasks. Since the data is only represented in a visual format, these occupations are out of reach for visually impaired people, making them unable to review hundreds of information-heavy cases per day and determine outcomes for each one in just a couple of minutes. In this work, we aim to shrink that gap by detailing the implementation of screen reader accessibility features to real-world visualizations used by fraud detection analysts. We propose a set of features that should be validated with users and, if proved to be useful, transformed into guidelines for creating these types of accessible charts.
Categorizing Uncertainties in the Process of Segmenting and Labeling Time Series Data
(The Eurographics Association, 2018) Bögl, Markus; Bors, Christian; Gschwandtner, Theresia; Miksch, Silvia; Anna Puig and Renata Raidou
The segmenting and labeling of multivariate time series data is applied in different domains, e.g. activity recognition or sensor states. This involves several steps of (pre-) processing, segmenting, and labeling of time intervals, and visually exploring the results as well as iteratively refining the parameters for all the processing steps. Within these processes different uncertainties are involved and relevant. In this poster we identify and categorize important uncertainties in this problem domain. We discuss challenges for visually communicating these uncertainties throughout the segmenting and labeling process.
The Challenge of Branch-Aware Data Manifold Exploration
(The Eurographics Association, 2023) Bot, Daniël M.; Peeters, Jannes; Aerts, Jan; Gillmann, Christina; Krone, Michael; Lenti, Simone
Branches within clusters can represent meaningful subgroups that should be explored. In general, automatically detecting branching structures within clusters requires analysing the distances between data points and a centrality metric, resulting in a complex two-dimensional hierarchy. This poster describes abstractions for this data and formulates requirements for a visualisation, building towards a comprehensive branch-aware cluster exploration interface.
Chord2DS: An Extension to Chord Diagram to Show Data Elements from Two Heterogeneous Data Sources
(The Eurographics Association, 2022) Humayoun, Shah Rukh; Brahmadevara, Likhitha; Krone, Michael; Lenti, Simone; Schmidt, Johanna
The standard Chord diagram, a radial layout, shows data elements in a circular fashion from one data source. In this paper, we propose an extension to the standard Chord diagram to show data elements from two heterogeneous data sources into one single diagram. The main Chord diagram is used for showing data elements and the relations between them from one data source, while we use an outer layer to show data elements from the second data source. The relationships between data elements from both data sources are shown through visual cues. The proposed solution uses space efficiently compared to using multiple diagrams in the scenarios of two heterogeneous data sources.
CitadelPolice: An Interactive Visualization Environment for Scenario Testing on Criminal Networks
(The Eurographics Association, 2023) Roelofsen, Liza A. S.; Oetker, Frederike; Lely, Miles van der; Belleman, Robert G.; Quax, Rick; Gillmann, Christina; Krone, Michael; Lenti, Simone
Criminal networks have proven to be highly resilient against law enforcement interventions. This resiliency has driven researchers to investigate these networks further. However, the obtained insights reaching law enforcement agencies are generally highly case-dependent or extremely general. Therefore, CitadelPolice aims to provide an environment for visualizing criminal network models on a comprehensive and interactive dashboard. The main advantage of CitadelPolice is that it allows law enforcement to independently test specific scenarios and discover the most effective disruption strategy before deploying it. To achieve this, we used a computational network model based on collaboration with and data from the Dutch Police Force, named the Criminal Cocaine Replacement Model and implemented this on a web-based graph visualization and simulation tool named Citadel. Using this, we can interactively visualize the network while running simulations. To test the effectiveness of the network visualization and implementation of the model, we performed sequential usability testing and compared the results over time.
CohExplore: Visually Supporting Students in Exploring Text Cohesion
(The Eurographics Association, 2023) Liebers, Carina; Agarwal, Shivam; Beck, Fabian; Gillmann, Christina; Krone, Michael; Lenti, Simone
A cohesive text allows readers to follow the described ideas and events. Exploring cohesion in text might aid students enhancing their academic writing. We introduce CohExplore, which promotes exploring and reflecting on cohesion of a given text by visualizing computed cohesion-related metrics on an overview and detailed level. Detected topics are color-coded, semantic similarity is shown via lines, while connectives and co-references in a paragraph are encoded using text decoration. Demonstrating the system, we share insights about a student-authored text.
Coloring Interactive Compositional Dot Maps
(The Eurographics Association, 2016) Tennekes, Martijn; Jonge, Edwin de; Tobias Isenberg and Filip Sadlo
We propose an algorithmic color scheme for zoom-able compositional dot maps. Contrary to existing methods, it uses density, composition, and zoom level to color the pixels of the resulting dot map. We describe the method and its application.
Comparative Analysis with Heightmaps in Virtual Reality Environments
(The Eurographics Association, 2019) Kraus, Matthias; Buchmüller, Juri; Schweitzer, Daniel; Keim, Daniel A.; Fuchs, Johannes; Madeiras Pereira, João and Raidou, Renata Georgia
3D heightmaps can be considered as an extension of heatmaps using the third dimension to encode the respective value by height, often in addition to encoding it by color. In contrast to 2D heatmaps, 3D heightmaps allow a superposition without aggregation. However, they also have the general disadvantages of 3D visualizations, such as occlusion and perceptual distortion. Previous research has revealed various advantages of stereoscopic displays and virtual reality (VR) in the context of 3D visualizations, for example, concerning memorization, depth perception, and collaboration. In this paper, we present a novel technique to compare heightmaps in VR by introducing a multi-layer approach of stacked heightmaps. We demonstrate the applicability and usefulness of our method by means of a use case on comparative crime data analysis.
Comparative Visualization of Longitudinal 24-hour Ambulatory Blood Pressure Measurements in Pediatric Patients with Chronic Kidney Disease
(The Eurographics Association, 2023) Özmen, Mahmut; Jabarulla, Mohamed Yaseen; Grabitz, Carl Robert; Melk, Anette; Wühl, Elke; Oeltze-Jafra, Steffen; Gillmann, Christina; Krone, Michael; Lenti, Simone
Pediatric chronic kidney disease (CKD) increases the risk of cardiovascular disease, stroke and other life-threatening conditions. Monitoring blood pressure in CKD patients is crucial to managing these risks. 24-hour ambulatory blood pressure monitoring (ABPM) is recommended for its comprehensive and accurate assessment of blood pressure over 24 hours. Analyzing and comparing 24-hour ABPM data of multiple diagnostic visits is a challenging task. Traditional methods involve comparing individual visits using paper printouts, which can be time-consuming and lacks a systematic overview of deviations over time. In this work, we present a dashboard visualization that allows clinicians (i) to assess the evolution of ABPM data over multiple diagnostic visits, (ii) to compare ABPM data of CKD patients with reference data of a healthy cohort, and (iii) to perform a detailed intra-individual comparison of the ABPM data acquired at two subsequent diagnostic visits. We demonstrate the dashboard in a case study of a patient with mild-to-moderate-stage CKD.
Constructing Hierarchical Continuity in Hilbert & Moore Treemaps
(The Eurographics Association, 2023) Scheibel, Willy; Döllner, Jürgen; Gillmann, Christina; Krone, Michael; Lenti, Simone
The Hilbert and Moore treemap layout algorithms are based on the space-filling Hilbert and Moore curves, respectively, to map tree-structured datasets to a 2D treemap layout. Considering multiple snapshots of a time-variant dataset, one of the design goals for Hilbert and Moore treemaps is layout stability, i.e., low changes in the layout for low changes in the underlying tree-structured data. For this, their underlying space-filling curve is expected to be continuous across all nodes and hierarchy levels, which has to be considered throughout the layouting process. We propose optimizations to subdivision templates, their orientation, and discuss the continuity of the underlying space-filling curve. We show real-world examples of Hilbert and Moore treemaps for small and large datasets with continuous space-filling curves, allowing for improved layout stability.
Context Specific Visualizations on Smartwatches
(The Eurographics Association, 2022) Islam, Alaul; Blascheck, Tanja; Isenberg, Petra; Krone, Michael; Lenti, Simone; Schmidt, Johanna
We present an analysis of the results of a full-day context-specific ideation exercise for smartwatch visualizations. Participants of the exercise created 34 sketches during a sightseeing activity. Our analysis of these sketches showed where visualizations could be applied and shown, what information needs they could target, and how data could be represented in the sightseeing context.
ConTraffic Visual Analytics in Support to Customs Risk-Analysis
(The Eurographics Association, 2017) Poulymenopoulou, Mikaela; Tsois, Aris; Anna Puig Puig and Tobias Isenberg
Customs risk analysis is crucial for detecting fraud and contraband goods in the massive flows of internationally traded goods. Most of non-bulk goods are transported in shipping containers and, as customs can control only about 2% of them, efficient customs risk analysis is crucial. In support to EU customs, the Joint Research Centre of the European Commission has developed the ConTraffic visual analytics research prototype. This paper presents the main architectural elements of the application and some visualization and user-interaction techniques selected to enable the route-based risk analysis of large number of shipping containers.
A Conversational Data Visualisation Platform for Hierarchical Multivariate Data
(The Eurographics Association, 2023) Kavaz, Ecem; Rodríguez, Inmaculada; Puig, Anna; Vives, Eduard; Gillmann, Christina; Krone, Michael; Lenti, Simone
This paper presents a novel data visualisation platform that integrates both direct manipulation and conversational interaction styles for analysing hierarchical multivariate data. The proposed architecture is based on the Rasa conversational AI framework. We show its full potential in a real-life case study for analysing hate speech in online news.

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