Now showing items 9-28 of 35

    • Enhancing Evaluation of Room Scale VR Studies to POI Visualizations in Minimaps 

      Ajdadilish, Batoul; Kohl, Steffi; Schröder, Kay (The Eurographics Association, 2022)
      Understanding and evaluating user behavior in virtual reality environments is challenging for researchers. Stereoscopic perception is highly dependent on the point of view, so it is necessary to account for multiple spatial ...
    • EuroVis 2022 Posters: Frontmatter 

      Krone, Michael; Lenti, Simone; Schmidt, Johanna (The Eurographics Association, 2022)
    • Exploration and Analysis of Image-base Simulation Ensembles 

      Dahshan, Mai; Turton, Terece L.; Polys, Nicholas (The Eurographics Association, 2022)
      Scientists run simulation ensembles to study the behavior of a phenomenon using varying initial conditions or input parameters. However, the I/O bottlenecks hinder performing large-scale multidimensional simulations. In ...
    • Explorative Visual Analysis of Spatio-temporal Regions to Detect Hemodynamic Biomarker Candidates 

      Derstroff, Adrian; Leistikow, Simon; Nahardani, Ali; Ebrahimi, Mahyasadat; Hoerr, Verena; Linsen, Lars (The Eurographics Association, 2022)
      Biomarkers are measurable biological properties that allow for distinguishing subjects of different cohorts such as healthy vs. diseased. In the context of diagnosing diseases of the cardiovascular system, researchers aim ...
    • GDot-i: Interactive System for Dot Paintings of Graphs 

      Eades, Peter; Hong, Seok-Hee; McGrane, Martin; Meidiana, Amyra (The Eurographics Association, 2022)
      This poster presents GDot-i, an interactive system visualizing graphs and networks as dot paintings, inspired by the dot painting style of Central Australia. We describe the implementation of GDot-i, a web-based interactive ...
    • Interactive Attribution-based Explanations for Image Segmentation 

      Humer, Christina; Elharty, Mohamed; Hinterreiter, Andreas; Streit, Marc (The Eurographics Association, 2022)
      Explanations of deep neural networks (DNNs) give users a better understanding of the inner workings and generalizability of a network. While the majority of research focuses on explanations for classification networks, in ...
    • Interactive Visualization of Machine Learning Model Results Predicting Infection Risk 

      Schäfer, Steffen; Baumgartl, Tom; Wulff, Antje; Kuijper, Arjan; Marschollek, Michael; Scheithauer, Simone; von Landesberger, Tatiana (The Eurographics Association, 2022)
      We present a novel visual-interactive interface to show results of a machine learning algorithm, which predicts the infection probability for patients in hospitals. The model result data is complex and needs to be presented ...
    • A Mental Workload Estimation for Visualization Evaluation Using EEG Data and NASA-TLX 

      Yim, Soobin; Yoon, Chanyoung; Yoo, Sangbong; Jang, Yun (The Eurographics Association, 2022)
      Mental workload is a cognitive effort felt by users while solving tasks, and good visualizations tend to induce a low mental workload. For better visualizations, various visualization techniques have been evaluated through ...
    • MOBS - Multi-Omics Brush for Subgraph Visualisation 

      Heylen, Dries; Peeters, Jannes; Ertaylan, Gökhan; Hooyberghs, Jef; Aerts, Jan (The Eurographics Association, 2022)
      One of the big opportunities in multi-omics analysis is the identification of interactions between molecular entities and their association with diseases. In analyzing and expressing these interactions in the search for ...
    • On Visualizing Music Storage Media for Modern Access to Historic Sources 

      Khulusi, Richard; Fricke, Heike (The Eurographics Association, 2022)
      Finding a balance between conserving historic objects and using them for research is one of the big issues in historic collections. Digitization holds the opportunity to offer a safe and non-destructible access to historic ...
    • Parameter Sensitivity and Uncertainty Visualization in DTI 

      Siddiqui, Faizan; Höllt, Thomas; Vilanova, Anna (The Eurographics Association, 2022)
      Diffusion Tensor Imaging is a powerful technique that provides a unique insight into the complex structure of the brain's white matter. However, several sources of uncertainty limit its widespread use. Data and modeling ...
    • PSEUDo: Interactive Pattern Search in Multivariate Time Series with Locality-Sensitive Hashing and Relevance Feedback 

      Yu, Yuncong; Kruyff, Dylan; Jiao, Jiao; Becker, Tim; Behrisch, Michael (The Eurographics Association, 2022)
      We present PSEUDo, a visual pattern retrieval tool for multivariate time series. It aims to overcome the uneconomic (re- )training with deep learning-based methods. Very high-dimensional time series emerge on an unprecedented ...
    • Scientific Convergence and Divergence in Visualization and Visual Analytics 

      He, Jiangen (The Eurographics Association, 2022)
      We present preliminary results of a visualization tool designed to visualize scientific evolution by using scientific publication data, especially convergence-divergence processes. It aims to increase the efficiency and ...
    • Situated Visualization in Motion for Video Games 

      Bucchieri, Federica; Yao, Lijie; Isenberg, Petra (The Eurographics Association, 2022)
      We contribute a systematic review of situated visualizations in motion in the context of video games. Video games produce rich dynamic datasets during gameplay that are often visualized to help players succeed in a game. ...
    • Sustainable Urban Wastewater Treatment Visualizations 

      Vega, Juan Marin; Uri-Carreño, Nerea; Kusnick, Jakob; Jänicke, Stefan (The Eurographics Association, 2022)
      The handling and treatment of urban wastewater are essential to protecting human health and the environment. However, its existence and importance are mostly invisible to the general public. In this work, we present a set ...
    • Toward an Interaction-Driven Framework for Modeling Big Data Visualization Systems 

      Benvenuti, Dario; Fiordeponti, Giovanni; Cheng, Hao; Catarci, Tiziana; Fekete, Jean-Daniel; Santucci, Giuseppe; Angelini, Marco; Battle, Leilani (The Eurographics Association, 2022)
      Designing big data visualization applications is challenging due to their complex yet isolated development. One of the most common issues is an increase in latency that can be experienced while interacting with the system. ...
    • Using Data Comics to Enhance Visualization Literacy 

      Boucher, Magdalena; Stoiber, Christina; Aigner, Wolfgang (The Eurographics Association, 2022)
      Visualization Literacy as a skill is becoming important, as growing amounts of data require complex ways of visualizing and interpreting them. Yet, it is hardly taught during general education, and not many resources ...
    • Validating Perception of Hyperspectral Textures in Virtual Reality Systems 

      Díaz-Barrancas, Francisco; Cwierz, Halina; Gil-Rodríguez, Raquel; Pardo, Pedro J. (The Eurographics Association, 2022)
      Virtual reality (VR) environments are increasingly offering higher quality content. They use different computing techniques to improve the final user experience. In this work, we create different light sources and introduce ...
    • Visual Exploration of Genetic Sequence Variants in Pangenomes 

      van den Brandt, Astrid; Jonkheer, Eef M.; van Workum, Dirk-Jan M.; Smit, Sandra; Vilanova, Anna (The Eurographics Association, 2022)
      To study the genetic sequence variation underlying traits of interest, the field of comparative genomics is moving away from analyses with single reference genomes to pangenomes; abstract representations of multiple genomes ...
    • Visual Exploration of Preference-based Routes in Ski Resorts 

      Rauscher, Julius; Miller, Matthias; Keim, Daniel A. (The Eurographics Association, 2022)
      Ski resorts exhibit a variety of available pistes and lifts, to which every skier has intrinsic preferences. While novices tend to favor easy pistes, experts might opt for more advanced pistes. In large resorts, the vast ...