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    Statistical Analysis of Parallel Data Uploading using OpenGL
    (The Eurographics Association, 2019) Wiedemann, Markus; Kranzlmüller, Dieter; Childs, Hank and Frey, Steffen
    Modern real-time visualizations of large-scale datasets require constant high frame rates while their datasets might exceed the available graphics memory. This requires sophisticated upload strategies from host memory to the memory of the graphics cards. A possible solution uses outsourcing of all data uploads onto concurrent threads and disconnecting prohibitive data dependencies. OpenGL provides a variety of functions and parameters but not all allow minimal interference on rendering. In this work, we present a thorough and statistically sound analysis of various effects introduced by choosing different input parameters, such as size, partitioning and number of threads for uploading, as well as combinations of buffer usage hints and uploading functions. This approach provides insight into the problem and offers a basis for future optimizations.
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    Rendering and Extracting Extremal Features in 3D Fields
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Kindlmann, Gordon L.; Chiw, Charisee; Huynh, Tri; Gyulassy, Attila; Reppy, John; Bremer, Peer-Timo; Jeffrey Heer and Heike Leitte and Timo Ropinski
    Visualizing and extracting three-dimensional features is important for many computational science applications, each with their own feature definitions and data types. While some are simple to state and implement (e.g. isosurfaces), others require more complicated mathematics (e.g. multiple derivatives, curvature, eigenvectors, etc.). Correctly implementing mathematical definitions is difficult, so experimenting with new features requires substantial investments. Furthermore, traditional interpolants rarely support the necessary derivatives, and approximations can reduce numerical stability. Our new approach directly translates mathematical notation into practical visualization and feature extraction, with minimal mental and implementation overhead. Using a mathematically expressive domain-specific language, Diderot, we compute direct volume renderings and particlebased feature samplings for a range of mathematical features. Non-expert users can experiment with feature definitions without any exposure to meshes, interpolants, derivative computation, etc. We demonstrate high-quality results on notoriously difficult features, such as ridges and vortex cores, using working code simple enough to be presented in its entirety.
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    Discrete Calabi Flow: A Unified Conformal Parameterization Method
    (The Eurographics Association and John Wiley & Sons Ltd., 2019) Su, Kehua; Li, Chenchen; Zhou, Yuming; Xu, Xu; Gu, Xianfeng; Lee, Jehee and Theobalt, Christian and Wetzstein, Gordon
    Conformal parameterization for surfaces into various parameter domains is a fundamental task in computer graphics. Prior research on discrete Ricci flow provided us with promising inspirations from methods derived via Riemannian geometry, which is rigorous in theory and effective in practice. In this paper, we propose a unified conformal parameterization approach for turning triangle meshes into planar and spherical domains using discrete Calabi flow on piecewise linear metric. We incorporate edgeflipping surgery to guarantee convergence as well as other significant improvements including approximate Newton's method, optimal step-lengths, priority embedding and boundary customizing, which achieve better performance and functionality with robustness and accuracy.
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    Visualization of 4D Vector Field Topology
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Hofmann, Lutz; Rieck, Bastian; Sadlo, Filip; Jeffrey Heer and Heike Leitte and Timo Ropinski
    In this paper, we present an approach to the topological analysis of four-dimensional vector fields. In analogy to traditional 2D and 3D vector field topology, we provide a classification and visual representation of critical points, together with a technique for extracting their invariant manifolds. For effective exploration of the resulting four-dimensional structures, we present a 4D camera that provides concise representation by exploiting projection degeneracies, and a 4D clipping approach that avoids self-intersection in the 3D projection. We exemplify the properties and the utility of our approach using specific synthetic cases.
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    A Multifragment Renderer for Material Aging Visualization
    (The Eurographics Association, 2018) Adamopoulos, Georgios; Moutafidou, Anastasia; Drosou, Anastasios; Tzovaras, Dimitrios; Fudos, Ioannis; Jain, Eakta and Kosinka, Jirí
    People involved in curatorial work and in preservation/conservation tasks need to understand exactly the nature of aging and to prevent it with minimal preservation work. In this scenario, it is of extreme importance to have tools to produce and visualize digital representations and models of visual surface appearance and material properties, to help the scientist understand how they evolve over time and under particular environmental conditions. We report on the development of a multifragment renderer for visualizing and combining the results of simulated aging of artwork objects. Several natural aging processes manifest themselves through change of color, fading, deformations or cracks. Furthermore, changes in the materials underneath the visible layers may be detected or simulated.
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    A Parallel Approach to Compression and Decompression of Triangle Meshes using the GPU
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Jakob, Johannes; Buchenau, Christoph; Guthe, Michael; Bærentzen, Jakob Andreas and Hildebrandt, Klaus
    Most state-of-the-art compression algorithms use complex connectivity traversal and prediction schemes, which are not efficient enough for online compression of large meshes. In this paper we propose a scalable massively parallel approach for compression and decompression of large triangle meshes using the GPU. Our method traverses the input mesh in a parallel breadth-first manner and encodes the connectivity data similarly to the well known cut-border machine. Geometry data is compressed using a local prediction strategy. In contrast to the original cut-border machine, we can additionally handle triangle meshes with inconsistently oriented faces. Our approach is more than one order of magnitude faster than currently used methods and achieves competitive compression rates.
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    HairControl: A Tracking Solution for Directable Hair Simulation
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Milliez, Antoine; Sumner, Robert W.; Gross, Markus; Thomaszewski, Bernhard; Thuerey, Nils and Beeler, Thabo
    We present a method for adding artistic control to physics-based hair simulation. Taking as input an animation of a coarse set of guide hairs, we constrain a subsequent higher-resolution simulation of detail hairs to follow the input motion in a spatially-averaged sense. The resulting high-resolution motion adheres to the artistic intent, but is enhanced with detailed deformations and dynamics generated by physics-based simulation. The technical core of our approach is formed by a set of tracking constraints, requiring the center of mass of a given subset of detail hair to maintain its position relative to a reference point on the corresponding guide hair. As a crucial element of our formulation, we introduce the concept of dynamicallychanging constraint targets that allow reference points to slide along the guide hairs to provide sufficient flexibility for natural deformations. We furthermore propose to regularize the null space of the tracking constraints based on variance minimization, effectively controlling the amount of spread in the hair. We demonstrate the ability of our tracking solver to generate directable yet natural hair motion on a set of targeted experiments and show its application to production-level animations.
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    Learning Physically Based Humanoid Climbing Movements
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Naderi, Kourosh; Babadi, Amin; Hämäläinen, Perttu; Thuerey, Nils and Beeler, Thabo
    We propose a novel learning-based solution for motion planning of physically-based humanoid climbing that allows for fast and robust planning of complex climbing strategies and movements, including extreme movements such as jumping. Similar to recent previous work, we combine a high-level graph-based path planner with low-level sampling-based optimization of climbing moves. We contribute through showing that neural network models of move success probability, effortfulness, and control policy can make both the high-level and low-level components more efficient and robust. The models can be trained through random simulation practice without any data. The models also eliminate the need for laboriously hand-tuned heuristics for graph search. As a result, we are able to efficiently synthesize climbing sequences involving dynamic leaps and one-hand swings, i.e. there are no limits to the movement complexity or the number of limbs allowed to move simultaneously. Our supplemental video also provides some comparisons between our AI climber and a real human climber.
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    Shading with Painterly Filtered Layers: A Technique to Obtain Painterly Portrait Animations
    (Association for Computing Machinery, Inc (ACM), 2017) Castaneda, Saif; Akleman, Ergun; Holger Winnemoeller and Lyn Bartram
    In this manuscript, we describe a process that can be used to create still and/or animated portrait paintings to be shown in Expressive Art Exhibit. Our process consists of two stages: (1) Creation of control textures for a Barycentric shader by using color information gathered from photographs to provide realistic looking skin rendering; (2) Filtering and compositing the layers of images that are obtained by control textures, which correspond to effects such as diffuse, specular and ambient. To demonstrate proof-of-concept, we have created a few rigid body animations of painterly portraits under different lighting conditions.
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    Constructing and Evaluating Visualisation Task Classifications: Process and Considerations
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Kerracher, Natalie; Kennedy, Jessie; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Categorising tasks is a common pursuit in the visualisation research community, with a wide variety of taxonomies, typologies, design spaces, and frameworks having been developed over the last three decades. While these classifications are universally purported to be useful in both the design and evaluation processes and in guiding future research, remarkably little attention has been paid to how these frameworks have-and can be-constructed and evaluated. In this paper we review the task classification literature and report on current practices in construction and evaluation. We consider the stages of task classification construction and identify the associated threats to validity arising at each stage and in response to the different methods employed. We provide guidance on suitable validation approaches in order to mitigate these threats. We also consider the appropriateness of evaluation strategies according to the different aspects of the classification which they evaluate. In so doing, we seek to provide guidance for developers of classifications in determining appropriate construction and evaluation strategies when developing a classification, and also for those selecting between competing classifications for use in the design and evaluation processes.