Now showing items 1-20 of 20

    • Learning a Perceptual Quality Metric for Correlation in Scatterplots 

      Wöhler, Leslie; Zou, Yuxin; Mühlhausen, Moritz; Albuquerque, Georgia; Magnor, Marcus (The Eurographics Association, 2019)
      Visual quality metrics describe the quality and efficiency of multidimensional data visualizations in order to guide data analysts during exploration tasks. Current metrics are usually based on empirical algorithms which ...
    • Visual Analytics of Simulation Ensembles for Network Dynamics 

      Ngo, Quynh Quang; Hütt, Marc-Thorsten; Linsen, Lars (The Eurographics Association, 2019)
      A central question in the field of Network Science is to analyze the role of a given network topology on the dynamical behavior captured by time-varying simulations executed on the network. These dynamical systems are also ...
    • Cluster-based Analysis of Multi-Parameter Distributions in Cloud Simulation Ensembles 

      Kumpf, Alexander; Stumpfegger, Josef; Westermann, Rüdiger (The Eurographics Association, 2019)
      The proposed approach enables a comparative visual exploration of multi-parameter distributions in time-varying 3D ensemble simulations. To investigate whether dominant trends in such distributions occur, we consider the ...
    • Consistent Filtering of Videos and Dense Light-Fields Without Optic-Flow 

      Shekhar, Sumit; Semmo, Amir; Trapp, Matthias; Tursun, Okan; Pasewaldt, Sebastian; Myszkowski, Karol; Döllner, Jürgen (The Eurographics Association, 2019)
      A convenient post-production video processing approach is to apply image filters on a per-frame basis. This allows the flexibility of extending image filters-originally designed for still images-to videos. However, per-image ...
    • A Visual Analytics Tool for Cohorts in Motion Data 

      Sheharyar, Ali; Ruh, Alexander; Valkov, Dimitar; Markl, Michael; Bouhali, Othmane; Linsen, Lars (The Eurographics Association, 2019)
      Motion data are curves over time in a 1D, 2D, or 3D space. To analyze sets of curves, machine learning methods can be applied to cluster them and detect outliers. However, often metadata or prior knowledge of the analyst ...
    • Stochastic Convolutional Sparse Coding 

      Xiong, Jinhui; Richtarik, Peter; Heidrich, Wolfgang (The Eurographics Association, 2019)
      State-of-the-art methods for Convolutional Sparse Coding usually employ Fourier-domain solvers in order to speed up the convolution operators. However, this approach is not without shortcomings. For example, Fourier-domain ...
    • Visualizing Transport and Mixing in Particle-based Fluid Flows 

      Rapp, Tobias; Dachsbacher, Carsten (The Eurographics Association, 2019)
      To gain insight into large, time-dependent particle-based fluid flows, we visually analyze Lagrangian coherent structures (LCS), a robust skeleton of the underlying particle dynamics. To identify these coherent structures, ...
    • Normal Map Bias Reduction for Many-Lights Multi-View Photometric Stereo 

      Gan, Jiangbin; Bergen, Philipp; Thormählen, Thorsten; Drescher, Philip; Hagens, Ralf (The Eurographics Association, 2019)
      In this paper, we improve upon an existing many-lights multi-view photometric stereo approach. Firstly, we show how to detect continuous regions for normal integration, which leads to a fully automatic reconstruction ...
    • Local Remote Photoplethysmography Signal Analysis for Application in Presentation Attack Detection 

      Kossack, Benjamin; Wisotzky, Eric L.; Hilsmann, Anna; Eisert, Peter (The Eurographics Association, 2019)
      This paper presents a method to analyze and visualize the local blood flow through human skin tissue within the face and neck. The method is based on the local signal characteristics and extracts and analyses the local ...
    • RodMesh: Two-handed 3D Surface Modeling in Virtual Reality 

      Verhoeven, Floor; Sorkine-Hornung, Olga (The Eurographics Association, 2019)
      User interfaces for 3D shape modeling in Virtual Reality (VR), unlike basic tasks such as text input and item selection, have been less explored in research so far. Shape modeling in 3D lends itself very well to VR, since ...
    • Open-Box Training of Kernel Support Vector Machines: Opportunities and Limitations 

      Khatami, Mohammad; Schultz, Thomas (The Eurographics Association, 2019)
      Kernel Support Vector Machines (SVMs) are widely used for supervised classification, and have achieved state-of-the-art performance in numerous applications. We aim to further increase their efficacy by allowing a human ...
    • Clustering Ensembles of 3D Jet-Stream Core Lines 

      Kern, Michael; Westermann, Rüdiger (The Eurographics Association, 2019)
      The extraction of a jet-stream core line in a wind field results in many disconnected line segments of arbitrary topology. In an ensemble of wind fields, these structures show high variation, coincide only partly, and ...
    • Visual Analysis of Probabilistic Infection Contagion in Hospitals 

      Wunderlich, Marcel; Block, Isabelle; von Landesberger, Tatiana; Petzold, Markus; Marschollek, Michael; Scheithauer, Simone (The Eurographics Association, 2019)
      Clinicians and hygienists need to know how an infection of one patient could be transmitted among other patients in the hospital (e.g., to prevent outbreaks). They need to analyze how many and which patients will possibly ...
    • Trigonometric Moments for Editable Structured Light Range Finding 

      Werner, Sebastian; Iseringhausen, Julian; Callenberg, Clara; Hullin, Matthias (The Eurographics Association, 2019)
      Structured-light methods remain one of the leading technologies in high quality 3D scanning, specifically for the acquisition of single objects and simple scenes. For more complex scene geometries, however, non-local light ...
    • VMV 2019: Frontmatter 

      Schulz, Hans-Jörg; Teschner, Matthias; Wimmer, Michael (Eurographics Association, 2019)
    • Joint Schedule and Layout Autotuning for Sparse Matrices with Compound Entries on GPUs 

      Mueller-Roemer, Johannes Sebastian; Stork, André; Fellner, Dieter W. (The Eurographics Association, 2019)
      Large sparse matrices with compound entries, i.e., complex and quaternionic matrices as well as matrices with dense blocks, are a core component of many algorithms in geometry processing, physically based animation, and ...
    • Polarization Demosaicking for Monochrome and Color Polarization Focal Plane Arrays 

      Qiu, Simeng; Fu, Qiang; Wang, Congli; Heidrich, Wolfgang (The Eurographics Association, 2019)
      Division-of-focal-plane (DoFP) polarization image sensors allow for snapshot imaging of linear polarization effects with inexpensive and straightforward setups. However, conventional interpolation based image reconstruction ...
    • Reflection Symmetry in Textured Sewing Patterns 

      Wolff, Katja; Herholz, Philipp; Sorkine-Hornung, Olga (The Eurographics Association, 2019)
      Recent work in the area of digital fabrication of clothes focuses on repetitive print patterns, specifically the 17 wallpaper groups, and their alignment along garment seams. While adjusting the underlying sewing patterns ...
    • Multi-Level-Memory Structures for Adaptive SPH Simulations 

      Winchenbach, Rene; Kolb, Andreas (The Eurographics Association, 2019)
      In this paper we introduce a novel hash map-based sparse data structure for highly adaptive Smoothed Particle Hydrodynamics (SPH) simulations on GPUs. Our multi-level-memory structure is based on stacking multiple independent ...
    • Reconfigurable Snapshot HDR Imaging Using Coded Masks and Inception Network 

      Alghamdi, Masheal; Fu, Qiang; Thabet, Ali; Heidrich, Wolfgang (The Eurographics Association, 2019)
      High Dynamic Range (HDR) image acquisition from a single image capture, also known as snapshot HDR imaging, is challenging because the bit depths of camera sensors are far from sufficient to cover the full dynamic range ...