Now showing items 1-16 of 16

    • A Compact Patch-Based Representation for Technical Mesh Models 

      Kammann, Lars; Menzel, Stefan; Botsch, Mario (The Eurographics Association, 2020)
      We present a compact and intuitive geometry representation for technical models initially given as triangle meshes. For CADlike models the defining features often coincide with the intersection between smooth surface ...
    • Data Reconstruction from Colored Slice-and-Dice Treemaps 

      Henkel, Markus; Knauthe, Volker; Landesberger, Tatiana von; Guthe, Stefan (The Eurographics Association, 2020)
      Treemaps illustrate hierarchical data, such as file systems or budget structures. Colors are often used to encode additional information or to emphasize the tree structure. Given a treemap, one may want to retrieve the ...
    • A Design and Application Space for Visualizing User Sessions of Virtual and Mixed Reality Environments 

      Agarwal, Shivam; Auda, Jonas; Schneegaß, Stefan; Beck, Fabian (The Eurographics Association, 2020)
      Virtual and mixed reality environments gain complexity due to the inclusion of multiple users and physical objects. A core challenge for developers and researchers while analyzing sessions from such environments lies in ...
    • Interactive Generation of 1D Embeddings from 2D Multi-dimensional Data Projections 

      Ngo, Quynh Quang; Linsen, Lars (The Eurographics Association, 2020)
      Visual analysis of multi-dimensional data is commonly supported by mapping the data to a 2D embedding. When analyzing a sequence of multi-dimensional data, e.g., in case of temporal data, the usage of 1D embeddings allows ...
    • Multi-Layer Alpha Tracing 

      Brüll, Felix; Grosch, Thorsten (The Eurographics Association, 2020)
      Rendering many transparent surfaces in real-time is still an open problem. We introduce two techniques for fast transparency rendering with ray tracing hardware, one being exact and the other being approximate but of high ...
    • Partial Matching of Trajectories with Particle Orientation for Exploratory Trajectory Visualization 

      Kahlert, Franziska; Gumhold, Stefan (The Eurographics Association, 2020)
      Trajectories of moving objects are of interest in multiple research fields ranging from geographic information science to behavioral science. Movement patterns of the studied object are often analyzed. Therefore, similar ...
    • Portal-Based Path Perturbation for Metropolis Light Transport 

      Otsu, Hisanari; Hanika, Johannes; Dachsbacher, Carsten (The Eurographics Association, 2020)
      Light transport simulation in scenes with difficult visibility still remains a challenging problem. Markov chain Monte Carlo (MCMC) rendering is often employed for such configurations. It generates a sequence of correlated ...
    • Real-time High-resolution Visualisation 

      Frieß, Florian; Müller, Christoph; Ertl, Thomas (The Eurographics Association, 2020)
      While visualisation often strives for abstraction, the interactive exploration of large scientific data sets like densely sampled 3D fields or massive particle data sets still benefits from rendering their graphical ...
    • Segmenting Computer-Tomographic Scans of Ancient Clay Artefacts for Visual Analysis of Cuneiform Inscriptions 

      Rolff, Tim; Rautenhaus, Marc; Olbrich, Stephan; Frintrop, Simone (The Eurographics Association, 2020)
      We address the automatic segmentation of computer tomographic scans of ancient clay tablets with cuneiform inscriptions enclosed inside a clay envelope. Such separation of parts of similar material properties in the scan ...
    • Static Visualization of Unsteady Flows by Flow Steadification 

      Wolligandt, Steve; Wilde, Thomas; Rössl, Christian; Theisel, Holger (The Eurographics Association, 2020)
      Finding static visual representations of time-varying phenomena is a standard problem in visualization. We are interested in unsteady flow data, i.e., we want to find a static visualization - one single still image - that ...
    • Visual Exploration of Cultural Heritage Collections with Linked Spatiotemporal, Shape and Metadata Views 

      Lengauer, Stefan; Komar, Alexander; Karl, Stephan; Trinkl, Elisabeth; Preiner, Reinhold; Schreck, Tobias (The Eurographics Association, 2020)
      The analysis of Cultural Heritage (CH) artefacts is an important task in the Digital Humanities. Increasingly, rich CH artefact data comprising metadata of different modalities becomes available in digital libraries and ...
    • Visualization Aided Interface Reconstruction 

      Penk, Dominik; Müller, Jonas; Felfer, Peter; Grosso, Roberto; Stamminger, Marc (The Eurographics Association, 2020)
      Modern atom probe tomography measurements generate large point clouds of atomic locations in solids. A common analysis task in these datasets is to put the location of specific atom types in relation to crystallographic ...
    • Visualization Framework for Assisting Interface Optimization of Hybrid Component Design 

      Kretzschmar, Vanessa; Gillmann, Christina; Günther, Fabian; Stommel, Markus; Scheuermann, Gerik (The Eurographics Association, 2020)
      Reliable component design is one of structural mechanics' main objectives. Especially for lightweight constructions, hybrid parts made of a multi-material combination are used. The design process for these parts often ...
    • Visualizing Sets and Changes in Membership Using Layered Set Intersection Graphs 

      Agarwal, Shivam; Tkachev, Gleb; Wermelinger, Michel; Beck, Fabian (The Eurographics Association, 2020)
      Challenges in set visualization include representing overlaps among sets, changes in their membership, and details of constituent elements. We present a visualization technique that addresses these challenges. The approach ...
    • VMV 2020: Frontmatter 

      Krüger, Jens; Niessner, Matthias; Stückler, Jörg (The Eurographics Association, 2020)
    • WLD: A Wavelet and Learning based Line Descriptor for Line Feature Matching 

      Lange, Manuel; Raisch, Claudio; Schilling, Andreas (The Eurographics Association, 2020)
      We present a machine learning based and wavelet enhanced line feature descriptor for line feature matching. Therefor we trained a neural network to compute a descriptor for a line, given preprocessed information from the ...