Volume 40 (2021)
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Item Temporally Dense Exploration of Moving and Deforming Shapes(© 2021 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2021) Frey, S.; Benes, Bedrich and Hauser, HelwigWe present our approach for the dense visualization and temporal exploration of moving and deforming shapes from scientific experiments and simulations. Our image space representation is created by convolving a noise texture along shape contours (akin to LIC). Beyond indicating spatial structure via luminosity, we additionally use colour to depict time or classes of shapes via automatically customized maps. This representation summarizes temporal evolution, and provides the basis for interactive user navigation in the spatial and temporal domain in combination with traditional renderings. Our efficient implementation supports the quick and progressive generation of our representation in parallel as well as adaptive temporal splits to reduce overlap. We discuss and demonstrate the utility of our approach using 2D and 3D scalar fields from experiments and simulations.Item Geodesic Distance Computation via Virtual Source Propagation(The Eurographics Association and John Wiley & Sons Ltd., 2021) Trettner, Philip; Bommes, David; Kobbelt, Leif; Digne, Julie and Crane, KeenanWe present a highly practical, efficient, and versatile approach for computing approximate geodesic distances. The method is designed to operate on triangle meshes and a set of point sources on the surface. We also show extensions for all kinds of geometric input including inconsistent triangle soups and point clouds, as well as other source types, such as lines. The algorithm is based on the propagation of virtual sources and hence easy to implement. We extensively evaluate our method on about 10000 meshes taken from the Thingi10k and the Tet Meshing in theWild data sets. Our approach clearly outperforms previous approximate methods in terms of runtime efficiency and accuracy. Through careful implementation and cache optimization, we achieve runtimes comparable to other elementary mesh operations (e.g. smoothing, curvature estimation) such that geodesic distances become a ''first-class citizen'' in the toolbox of geometric operations. Our method can be parallelized and we observe up to 6x speed-up on the CPU and 20x on the GPU. We present a number of mesh processing tasks easily implemented on the basis of fast geodesic distances. The source code of our method is provided as a C++ library under the MIT license.Item Egocentric Network Exploration for Immersive Analytics(The Eurographics Association and John Wiley & Sons Ltd., 2021) Sorger, Johannes; Arleo, Alessio; Kán, Peter; Knecht, Wolfgang; Waldner, Manuela; Zhang, Fang-Lue and Eisemann, Elmar and Singh, KaranTo exploit the potential of immersive network analytics for engaging and effective exploration, we promote the metaphor of ''egocentrism'', where data depiction and interaction are adapted to the perspective of the user within a 3D network. Egocentrism has the potential to overcome some of the inherent downsides of virtual environments, e.g., visual clutter and cyber-sickness. To investigate the effect of this metaphor on immersive network exploration, we designed and evaluated interfaces of varying degrees of egocentrism. In a user study, we evaluated the effect of these interfaces on visual search tasks, efficiency of network traversal, spatial orientation, as well as cyber-sickness. Results show that a simple egocentric interface considerably improves visual search efficiency and navigation performance, yet does not decrease spatial orientation or increase cyber-sickness. An occlusion-free Ego-Bubble view of the neighborhood only marginally improves the user's performance. We tie our findings together in an open online tool for egocentric network exploration, providing actionable insights on the benefits of the egocentric network exploration metaphorItem Parametric Skeletons with Reduced Soft‐Tissue Deformations(© 2021 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2021) Tapia, Javier; Romero, Cristian; Pérez, Jesús; Otaduy, Miguel A.; Benes, Bedrich and Hauser, HelwigWe present a method to augment parametric skeletal models with subspace soft‐tissue deformations. We combine the benefits of data‐driven skeletal models, i.e. accurate replication of contact‐free static deformations, with the benefits of pure physics‐based models, i.e. skin and skeletal reaction to contact and inertial motion with two‐way coupling. We succeed to do so in a highly efficient manner, thanks to a careful choice of reduced model for the subspace deformation. With our method, it is easy to design expressive reduced models with efficient yet accurate force computations, without the need for training deformation examples. We demonstrate the application of our method to parametric models of human bodies, SMPL, and hands, MANO, with interactive simulations of contact with nonlinear soft‐tissue deformation and skeletal response.>Item Patch Erosion for Deformable Lapped Textures on 3D Fluids(The Eurographics Association and John Wiley & Sons Ltd., 2021) Gagnon, Jonathan; Guzmán, Julián E.; Mould, David; Paquette, Eric; Mitra, Niloy and Viola, IvanWe propose an approach to synthesise a texture on an animated fluid free surface using a distortion metric combined with a feature map. Our approach is applied as a post-process to a fluid simulation. We advect deformable patches to move the texture along the fluid flow. The patches are covering the whole surface every frame of the animation in an overlapping fashion. Using lapped textures combined with deformable patches, we successfully remove blending artifact and rigid artifact seen in previous methods. We remain faithful to the texture exemplar by removing distorted patch texels using a patch erosion process. The patch erosion is based on a feature map provided together with the exemplar as inputs to our approach. The erosion favors removing texels toward the boundary of the patch as well as texels corresponding to more distorted regions of the patch. Where texels are removed leaving a gap on the surface, we add new patches below existing ones. The result is an animated texture following the velocity field of the fluid. We compared our results with recent work and our results show that our approach removes ghosting and temporal fading artifacts.Item A Multi-pass Method for Accelerated Spectral Sampling(The Eurographics Association and John Wiley & Sons Ltd., 2021) Ruit, Mark van de; Eisemann, Elmar; Zhang, Fang-Lue and Eisemann, Elmar and Singh, KaranSpectral Monte Carlo rendering can simulate advanced light phenomena, such as chromatic dispersion, but typically shows a slow convergence behavior. Properly sampling the spectral domain can be challenging in scenes with many complex spectral distributions. To this end, we propose a multi-pass approach. We build and store coarse screen-space estimates of incident spectral radiance and use these to then importance sample the spectral domain. Hereby, we lower variance and reduce noise with little overhead. Our method handles challenging scenarios with difficult spectral distributions, many different emitters, and participating media. Finally, it can be integrated into existing spectral rendering methods for an additional acceleration.Item Spatiotemporal Texture Reconstruction for Dynamic Objects Using a Single RGB-D Camera(The Eurographics Association and John Wiley & Sons Ltd., 2021) Kim, Hyomin; Kim, Jungeon; Nam, Hyeonseo; Park, Jaesik; Lee, Seungyong; Mitra, Niloy and Viola, IvanThis paper presents an effective method for generating a spatiotemporal (time-varying) texture map for a dynamic object using a single RGB-D camera. The input of our framework is a 3D template model and an RGB-D image sequence. Since there are invisible areas of the object at a frame in a single-camera setup, textures of such areas need to be borrowed from other frames. We formulate the problem as an MRF optimization and define cost functions to reconstruct a plausible spatiotemporal texture for a dynamic object. Experimental results demonstrate that our spatiotemporal textures can reproduce the active appearances of captured objects better than approaches using a single texture map.Item SketchZooms: Deep Multi‐view Descriptors for Matching Line Drawings(© 2021 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2021) Navarro, Pablo; Orlando, J. Ignacio; Delrieux, Claudio; Iarussi, Emmanuel; Benes, Bedrich and Hauser, HelwigFinding point‐wise correspondences between images is a long‐standing problem in image analysis. This becomes particularly challenging for sketch images, due to the varying nature of human drawing style, projection distortions and viewport changes. In this paper, we present the first attempt to obtain a learned descriptor for dense registration in line drawings. Based on recent deep learning techniques for corresponding photographs, we designed descriptors to locally match image pairs where the object of interest belongs to the same semantic category, yet still differ drastically in shape, form, and projection angle. To this end, we have specifically crafted a data set of synthetic sketches using non‐photorealistic rendering over a large collection of part‐based registered 3D models. After training, a neural network generates descriptors for every pixel in an input image, which are shown togeneralize correctly in unseen sketches hand‐drawn by humans. We evaluate our method against a baseline of correspondences data collected from expert designers, in addition to comparisons with other descriptors that have been proven effective in sketches. Code, data and further resources will be publicly released by the time of publication.Item Animated Presentation of Static Infographics with InfoMotion(The Eurographics Association and John Wiley & Sons Ltd., 2021) Wang, Yun; Gao, Yi; Huang, Ray; Cui, Weiwei; Zhang, Haidong; Zhang, Dongmei; Borgo, Rita and Marai, G. Elisabeta and Landesberger, Tatiana vonBy displaying visual elements logically in temporal order, animated infographics can help readers better understand layers of information expressed in an infographic. While many techniques and tools target the quick generation of static infographics, few support animation designs. We propose InfoMotion that automatically generates animated presentations of static infographics. We first conduct a survey to explore the design space of animated infographics. Based on this survey, InfoMotion extracts graphical properties of an infographic to analyze the underlying information structures; then, animation effects are applied to the visual elements in the infographic in temporal order to present the infographic. The generated animations can be used in data videos or presentations. We demonstrate the utility of InfoMotion with two example applications, including mixed-initiative animation authoring and animation recommendation. To further understand the quality of the generated animations, we conduct a user study to gather subjective feedback on the animations generated by InfoMotion.Item RigidFusion: RGB-D Scene Reconstruction with Rigidly-moving Objects(The Eurographics Association and John Wiley & Sons Ltd., 2021) Wong, Yu-Shiang; Li, Changjian; Nießner, Matthias; Mitra, Niloy J.; Mitra, Niloy and Viola, IvanAlthough surface reconstruction from depth data has made significant advances in the recent years, handling changing environments remains a major challenge. This is unsatisfactory, as humans regularly move objects in their environments. Existing solutions focus on a restricted set of objects (e.g., those detected by semantic classifiers) possibly with template meshes, assume static camera, or mark objects touched by humans as moving. We remove these assumptions by introducing RigidFusion. Our core idea is a novel asynchronous moving-object detection method, combined with a modified volumetric fusion. This is achieved by a model-to-frame TSDF decomposition leveraging free-space carving of tracked depth values of the current frame with respect to the background model during run-time. As output, we produce separate volumetric reconstructions for the background and each moving object in the scene, along with its trajectory over time. Our method does not rely on the object priors (e.g., semantic labels or pre-scanned meshes) and is insensitive to the motion residuals between objects and the camera. In comparison to state-of-the-art methods (e.g., Co-Fusion, MaskFusion), we handle significantly more challenging reconstruction scenarios involving moving camera and improve moving-object detection (26% on the miss-detection ratio), tracking (27% on MOTA), and reconstruction (3% on the reconstruction F1) on the synthetic dataset. Please refer the supplementary and the project website for the video demonstration (geometry.cs.ucl.ac.uk/projects/2021/rigidfusion).Item What are Table Cartograms Good for Anyway? An Algebraic Analysis(The Eurographics Association and John Wiley & Sons Ltd., 2021) McNutt, Andrew; Borgo, Rita and Marai, G. Elisabeta and Landesberger, Tatiana vonUnfamiliar or esoteric visual forms arise in many areas of visualization. While such forms can be intriguing, it can be unclear how to make effective use of them without long periods of practice or costly user studies. In this work we analyze the table cartogram-a graphic which visualizes tabular data by bringing the areas of a grid of quadrilaterals into correspondence with the input data, like a heat map that has been ''area-ed'' rather than colored. Despite having existed for several years, little is known about its appropriate usage. We mend this gap by using Algebraic Visualization Design to show that they are best suited to relatively small tables with ordinal axes for some comparison and outlier identification tasks. In doing so we demonstrate a discount theory-based analysis that can be used to cheaply determine best practices for unknown visualizations.Item Learning Direction Fields for Quad Mesh Generation(The Eurographics Association and John Wiley & Sons Ltd., 2021) Dielen, Alexander; Lim, Isaak; Lyon, Max; Kobbelt, Leif; Digne, Julie and Crane, KeenanState of the art quadrangulation methods are able to reliably and robustly convert triangle meshes into quad meshes. Most of these methods rely on a dense direction field that is used to align a parametrization from which a quad mesh can be extracted. In this context, the aforementioned direction field is of particular importance, as it plays a key role in determining the structure of the generated quad mesh. If there are no user-provided directions available, the direction field is usually interpolated from a subset of principal curvature directions. To this end, a number of heuristics that aim to identify significant surface regions have been proposed. Unfortunately, the resulting fields often fail to capture the structure found in meshes created by human experts. This is due to the fact that experienced designers can leverage their domain knowledge in order to optimize a mesh for a specific application. In the context of physics simulation, for example, a designer might prefer an alignment and local refinement that facilitates a more accurate numerical simulation. Similarly, a character artist may prefer an alignment that makes the resulting mesh easier to animate. Crucially, this higher level domain knowledge cannot be easily extracted from local curvature information alone. Motivated by this issue, we propose a data-driven approach to the computation of direction fields that allows us to mimic the structure found in existing meshes, which could originate from human experts or other sources. More specifically, we make use of a neural network that aggregates global and local shape information in order to compute a direction field that can be used to guide a parametrization-based quad meshing method. Our approach is a first step towards addressing this challenging problem with a fully automatic learning-based method. We show that compared to classical techniques our data-driven approach combined with a robust model-driven method, is able to produce results that more closely exhibit the ground truth structure of a synthetic dataset (i.e. a manually designed quad mesh template fitted to a variety of human body types in a set of different poses).Item Cooperative Profile Guided Optimizations(The Eurographics Association and John Wiley & Sons Ltd., 2021) Stephenson, Mark; Rangan, Ram; Keckler, Stephen W.; Binder, Nikolaus and Ritschel, TobiasExisting feedback-driven optimization frameworks are not suitable for video games, which tend to push the limits of performance of gaming platforms and have real-time constraints that preclude all but the simplest execution profiling. While Profile Guided Optimization (PGO) is a well-established optimization approach, existing PGO techniques are ill-suited for games for a number of reasons, particularly because heavyweight profiling makes interactive applications unresponsive. Adaptive optimization frameworks continually collect metrics that guide code specialization optimizations during program execution but have similarly high overheads. We emulate a system, which we call Cooperative PGO, in which the gaming platform collects piecemeal profiles by sampling in both time and space during actual gameplay across many users; stitches the piecemeal profiles together statistically; and creates policies to guide future gameplay. We introduce a three-level hierarchical profiler that is well-suited to graphics APIs, that commonly operates with no overhead and occasionally introduces an average overhead of less than 0.5% during periods of active profiling. This paper examines the practicality of Cooperative PGO using three PGOs as case studies. A PGO that exploits likely zeros is particularly effective, achieving an average speedup of 5%, with a maximum speedup of 15%, over a highly-tuned baseline.Item EUROGRAPHICS 2021: CGF 40-2 Frontmatter(The Eurographics Association and John Wiley & Sons Ltd., 2021) Mitra, Niloy; Viola, Ivan; Mitra, Niloy and Viola, Ivan-Item Global Illumination-Aware Stylised Shading(The Eurographics Association and John Wiley & Sons Ltd., 2021) Doi, Kohei; Morimoto, Yuki; Tsuruno, Reiji; Zhang, Fang-Lue and Eisemann, Elmar and Singh, KaranOur aim is to convert an object's appearance to an arbitrary colour considering the light scattering in the entire scene, which is often called the global illumination. Existing stylisation methods convert the colour of an object with a 1-dimensional texture for 3-dimensional computer graphics to reproduce a typical style used in illustrations and cel animations. However, they cannot express global illumination effects. We propose two individual methods to compute the global illumination and convert the shading to an arbitrary colour. The methods reproduce reflections in other objects with the converted colour. As a result, we can convert the colour of illumination effects that have not yet been reproduced, such as soft shadows and refractionsItem Deep Portrait Lighting Enhancement with 3D Guidance(The Eurographics Association and John Wiley & Sons Ltd., 2021) Han, Fangzhou; Wang, Can; Du, Hao; Liao, Jing; Bousseau, Adrien and McGuire, MorganDespite recent breakthroughs in deep learning methods for image lighting enhancement, they are inferior when applied to portraits because 3D facial information is ignored in their models. To address this, we present a novel deep learning framework for portrait lighting enhancement based on 3D facial guidance. Our framework consists of two stages. In the first stage, corrected lighting parameters are predicted by a network from the input bad lighting image, with the assistance of a 3D morphable model and a differentiable renderer. Given the predicted lighting parameter, the differentiable renderer renders a face image with corrected shading and texture, which serves as the 3D guidance for learning image lighting enhancement in the second stage. To better exploit the long-range correlations between the input and the guidance, in the second stage, we design an imageto- image translation network with a novel transformer architecture, which automatically produces a lighting-enhanced result. Experimental results on the FFHQ dataset and in-the-wild images show that the proposed method outperforms state-of-the-art methods in terms of both quantitative metrics and visual quality.Item A Visual Designer of Layer-wise Relevance Propagation Models(The Eurographics Association and John Wiley & Sons Ltd., 2021) Huang, Xinyi; Jamonnak, Suphanut; Zhao, Ye; Wu, Tsung Heng; Xu, Wei; Borgo, Rita and Marai, G. Elisabeta and Landesberger, Tatiana vonLayer-wise Relevance Propagation (LRP) is an emerging and widely-used method for interpreting the prediction results of convolutional neural networks (CNN). LRP developers often select and employ different relevance backpropagation rules and parameters, to compute relevance scores on input images. However, there exists no obvious solution to define a ''best'' LRP model. A satisfied model is highly reliant on pertinent images and designers' goals. We develop a visual model designer, named as VisLRPDesigner, to overcome the challenges in the design and use of LRP models. Various LRP rules are unified into an integrated framework with an intuitive workflow of parameter setup. VisLRPDesigner thus allows users to interactively configure and compare LRP models. It also facilitates relevance-based visual analysis with two important functions: relevance-based pixel flipping and neuron ablation. Several use cases illustrate the benefits of VisLRPDesigner. The usability and limitation of the visual designer is evaluated by LRP users.Item Visual Analysis of Electronic Densities and Transitions in Molecules(The Eurographics Association and John Wiley & Sons Ltd., 2021) Masood, Talha Bin; Thygesen, Signe Sidwall; Linares, Mathieu; Abrikosov, Alexei I.; Natarajan, Vijay; Hotz, Ingrid; Borgo, Rita and Marai, G. Elisabeta and Landesberger, Tatiana vonThe study of electronic transitions within a molecule connected to the absorption or emission of light is a common task in the process of the design of new materials. The transitions are complex quantum mechanical processes and a detailed analysis requires a breakdown of these processes into components that can be interpreted via characteristic chemical properties. We approach these tasks by providing a detailed analysis of the electron density field. This entails methods to quantify and visualize electron localization and transfer from molecular subgroups combining spatial and abstract representations. The core of our method uses geometric segmentation of the electronic density field coupled with a graph-theoretic formulation of charge transfer between molecular subgroups. The design of the methods has been guided by the goal of providing a generic and objective analysis following fundamental concepts. We illustrate the proposed approach using several case studies involving the study of electronic transitions in different molecular systems.Item ParSetgnostics: Quality Metrics for Parallel Sets(The Eurographics Association and John Wiley & Sons Ltd., 2021) Dennig, Frederik L.; Fischer, Maximilian T.; Blumenschein, Michael; Fuchs, Johannes; Keim, Daniel A.; Dimara, Evanthia; Borgo, Rita and Marai, G. Elisabeta and Landesberger, Tatiana vonWhile there are many visualization techniques for exploring numeric data, only a few work with categorical data. One prominent example is Parallel Sets, showing data frequencies instead of data points - analogous to parallel coordinates for numerical data. As nominal data does not have an intrinsic order, the design of Parallel Sets is sensitive to visual clutter due to overlaps, crossings, and subdivision of ribbons hindering readability and pattern detection. In this paper, we propose a set of quality metrics, called ParSetgnostics (Parallel Sets diagnostics), which aim to improve Parallel Sets by reducing clutter. These quality metrics quantify important properties of Parallel Sets such as overlap, orthogonality, ribbon width variance, and mutual information to optimize the category and dimension ordering. By conducting a systematic correlation analysis between the individual metrics, we ensure their distinctiveness. Further, we evaluate the clutter reduction effect of ParSetgnostics by reconstructing six datasets from previous publications using Parallel Sets measuring and comparing their respective properties. Our results show that ParSetgostics facilitates multi-dimensional analysis of categorical data by automatically providing optimized Parallel Set designs with a clutter reduction of up to 81% compared to the originally proposed Parallel Sets visualizations.Item Geometry Processing 2021 CGF 40-5: Frontmatter(The Eurographics Association and John Wiley & Sons Ltd., 2021) Digne, Julie; Crane, Keenan; Digne, Julie and Crane, Keenan