Volume 39 (2020)

Permanent URI for this community

https://diglib.eg.org/handle/10.2312/2632879

Browse

Now showing 1 - 20 of 297

Visualizing Dynamics of Urban Regions Through a Geo‐Semantic Graph‐Based Method
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Wang, Yunzhe; Baciu, George; Li, Chenhui; Benes, Bedrich and Hauser, Helwig
In urban analysis, it is desirable to find regions where a primary socio‐economic activity dominates as a key endeavour. This can be accomplished by aggregating neighbouring locations where similar activities take place. However, people move and their activities change over time. Furthermore, the boundaries of regions are not stationary. Thus, it is challenging to update region divisions and track their evolution. Geo‐textual data embody geographical information and activity descriptions. We obtain changes in regional boundaries by iteratively applying a process to a sequence of latent graphs that are constructed from geo‐textual data. Region characteristics are interpreted by topics learned by the latent Dirichlet allocation model. We also propose a matching algorithm to expose region transformations between different timestamps. Interesting patterns of evolution emerge after clustering the migration trajectories of region centroids. In our visual system, users can explore the evolution of regions through animations and linked snapshots. To facilitate visual comparisons, we represent regions by hexagonal tiling that better construct arbitrary regional shapes. The effectiveness of our method is evaluated on two case studies using real‐world datasets, and a user study shows that our visual analytics system is highly effective in performing studies on such regional maps.
Physically Based Real‐Time Rendering of Teeth and Partial Restorations
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Reischl, M.; Derzapf, E.; Guthe, M.; Benes, Bedrich and Hauser, Helwig
Visually accurate real‐time rendering of teeth has many applications ranging from computer games to dental computer aided design (CAD). Similar to skin, the realistic and physically correct appearance of teeth cannot be achieved by simply using opaque diffuse textures, mainly because of the subsurface scattering behaviours of both. While both have a layered structure in common, the scattering characteristics of the teeth layers are drastically different from those of the skin, making rendering much more complicated. We present an approach which uses the Henyey–Greenstein scattering to achieve a near realistic real‐time rendering of human teeth. To simulate the multi‐layered geometry of teeth, we use standardized teeth models with dentin cores and fit them to real scanned teeth or dental restorations. By using a proxy geometry to compute the scattering, we can also render partial restorations as they would look like when attached to the remaining teeth. Finally, we compare our results to the VITA shade systems and human teeth to evaluate the visual fidelity of our approach.
A Parametric Analysis of Discrete Hamiltonian Functional Maps
(The Eurographics Association and John Wiley & Sons Ltd., 2020) Postolache, Emilian; Fumero, Marco; Cosmo, Luca; Rodolà, Emanuele; Jacobson, Alec and Huang, Qixing
In this paper we develop an in-depth theoretical investigation of the discrete Hamiltonian eigenbasis, which remains quite unexplored in the geometry processing community. This choice is supported by the fact that Dirichlet eigenfunctions can be equivalently computed by defining a Hamiltonian operator, whose potential energy and localization region can be controlled with ease. We vary with continuity the potential energy and study the relationship between the Dirichlet Laplacian and the Hamiltonian eigenbases with the functional map formalism. We develop a global analysis to capture the asymptotic behavior of the eigenpairs. We then focus on their local interactions, namely the veering patterns that arise between proximal eigenvalues. Armed with this knowledge, we are able to track the eigenfunctions in all possible configurations, shedding light on the nature of the functional maps. We exploit the Hamiltonian-Dirichlet connection in a partial shape matching problem, obtaining state of the art results, and provide directions where our theoretical findings could be applied in future research.
Detection and Synthesis of Full‐Body Environment Interactions for Virtual Humans
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Juarez‐Perez, A.; Kallmann, M.; Benes, Bedrich and Hauser, Helwig
We present a new methodology for enabling virtual humans to autonomously detect and perform complex full‐body interactions with their environments. Given a parameterized walking controller and a set of motion‐captured example interactions, our method is able to detect when interactions can occur and to coordinate the detected upper‐body interaction with the walking controller in order to achieve full‐body mobile interactions in similar situations. Our approach is based on learning spatial coordination features from the example motions and on associating body‐environment proximity information to the body configurations of each performed action. Body configurations become the input to a regression system, which in turn is able to generate new interactions for different situations in similar environments. The regression model is capable of selecting, encoding and replicating key spatial strategies with respect to body coordination and management of environment constraints as well as determining the correct moment in time and space for starting an interaction. As a result, we obtain an interactive controller able to detect and synthesize coordinated full‐body motions for a variety of complex interactions requiring body mobility. Our results achieve complex interactions, such as opening doors and drawing in a wide whiteboard. The presented approach introduces the concept of learning interaction coordination models that can be applied on top of any given walking controller. The obtained method is simple and flexible, it handles the detection of possible interactions and is suitable for real‐time applications.
Monocular Human Pose and Shape Reconstruction using Part Differentiable Rendering
(The Eurographics Association and John Wiley & Sons Ltd., 2020) Wang, Min; Qiu, Feng; Liu, Wentao; Qian, Chen; Zhou, Xiaowei; Ma, Lizhuang; Eisemann, Elmar and Jacobson, Alec and Zhang, Fang-Lue
Superior human pose and shape reconstruction from monocular images depends on removing the ambiguities caused by occlusions and shape variance. Recent works succeed in regression-based methods which estimate parametric models directly through a deep neural network supervised by 3D ground truth. However, 3D ground truth is neither in abundance nor can efficiently be obtained. In this paper, we introduce body part segmentation as critical supervision. Part segmentation not only indicates the shape of each body part but helps to infer the occlusions among parts as well. To improve the reconstruction with part segmentation, we propose a part-level differentiable renderer that enables part-based models to be supervised by part segmentation in neural networks or optimization loops. We also introduce a general parametric model engaged in the rendering pipeline as an intermediate representation between skeletons and detailed shapes, which consists of primitive geometries for better interpretability. The proposed approach combines parameter regression, body model optimization, and detailed model registration altogether. Experimental results demonstrate that the proposed method achieves balanced evaluation on pose and shape, and outperforms the state-of-the-art approaches on Human3.6M, UP-3D and LSP datasets.
Can't Invert the CDF? The Triangle-Cut Parameterization of the Region under the Curve
(The Eurographics Association and John Wiley & Sons Ltd., 2020) Heitz, Eric; Dachsbacher, Carsten and Pharr, Matt
We present an exact, analytic and deterministic method for sampling densities whose Cumulative Distribution Functions (CDFs) cannot be inverted analytically. Indeed, the inverse-CDF method is often considered the way to go for sampling non-uniform densities. If the CDF is not analytically invertible, the typical fallback solutions are either approximate, numerical, or nondeterministic such as acceptance-rejection. To overcome this problem, we show how to compute an analytic area-preserving parameterization of the region under the curve of the target density. We use it to generate random points uniformly distributed under the curve of the target density and their abscissae are thus distributed with the target density. Technically, our idea is to use an approximate analytic parameterization whose error can be represented geometrically as a triangle that is simple to cut out. This triangle-cut parameterization yields exact and analytic solutions to sampling problems that were presumably not analytically resolvable.
Representative Isovalue Detection and Isosurface Segmentation Using Novel Isosurface Measures
(The Eurographics Association and John Wiley & Sons Ltd., 2020) Wang, Cuilan; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
Interval volume is the volume of the region between two isosurfaces. This paper proposes a novel measure, called VOA measure, that is computed based on interval volume and isosurface area. This measure represents the rate of change of distance between isosurfaces with respect to isovalue. It can be used to detect representative isovalues of the dataset since two isosurfaces near material boundaries tend to be much closer to each other than two isosurfaces in material interiors, assuming they have the same isovalue difference. For the same isosurface, some portion of it may pass through the boundary of two materials and some portion of it may pass through the interior of a material. To separate the portions of an isosurface that represent different features of the dataset, another novel isosurface measure is introduced. This measure is calculated based on the Euclidean distance of individual sample points on two isosurfaces. The effectiveness of the two new measures in detecting significant isovalues and segmenting isosurfaces are demonstrated in the paper.
EGGS: Sparsity-Specific Code Generation
(The Eurographics Association and John Wiley & Sons Ltd., 2020) Tang, Xuan; Schneider, Teseo; Kamil, Shoaib; Panda, Aurojit; Li, Jinyang; Panozzo, Daniele; Jacobson, Alec and Huang, Qixing
Sparse matrix computations are among the most important computational patterns, commonly used in geometry processing, physical simulation, graph algorithms, and other situations where sparse data arises. In many cases, the structure of a sparse matrix is known a priori, but the values may change or depend on inputs to the algorithm. We propose a new methodology for compile-time specialization of algorithms relying on mixing sparse and dense linear algebra operations, using an extension to the widely-used open source Eigen package. In contrast to library approaches optimizing individual building blocks of a computation (such as sparse matrix product), we generate reusable sparsity-specific implementations for a given algorithm, utilizing vector intrinsics and reducing unnecessary scanning through matrix structures. We demonstrate the effectiveness of our technique on a benchmark of artificial expressions to quantitatively evaluate the benefit of our approach over the state-ofthe- art library Intel MKL. To further demonstrate the practical applicability of our technique we show that our technique can improve performance, with minimal code changes, for mesh smoothing, mesh parametrization, volumetric deformation, optical flow, and computation of the Laplace operator.
Metro Maps on Octilinear Grid Graphs
(The Eurographics Association and John Wiley & Sons Ltd., 2020) Bast, Hannah; Brosi, Patrick; Storandt, Sabine; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
Schematic transit maps (often called "metro maps" in the literature) are important to produce comprehensible visualizations of complex public transit networks. In this work, we investigate the problem of automatically drawing such maps on an octilinear grid with an arbitrary (but optimal) number of edge bends. Our approach can naturally deal with obstacles that should be respected in the final drawing (points of interest, rivers, coastlines) and can prefer grid edges near the real-world course of a line. This allows our drawings to be combined with existing maps, for example as overlays in map services. We formulate an integer linear program which can be used to solve the problem exactly. We also provide a fast approximation algorithm which greedily calculates shortest paths between node candidates on the underlying octilinear grid graph. Previous work used local search techniques to update node positions until a local optimum was found, but without guaranteeing octilinearity. We can thus calculate nearly optimal metro maps in a fraction of a second even for complex networks, enabling the interactive use of our method in map editors.
A Practical Method for Animating Anisotropic Elastoplastic Materials
(The Eurographics Association and John Wiley & Sons Ltd., 2020) Schreck, Camille; Wojtan, Chris; Panozzo, Daniele and Assarsson, Ulf
This paper introduces a simple method for simulating highly anisotropic elastoplastic material behaviors like the dissolution of fibrous phenomena (splintering wood, shredding bales of hay) and materials composed of large numbers of irregularly-shaped bodies (piles of twigs, pencils, or cards). We introduce a simple transformation of the anisotropic problem into an equivalent isotropic one, and we solve this new ''fictitious'' isotropic problem using an existing simulator based on the material point method. Our approach results in minimal changes to existing simulators, and it allows us to re-use popular isotropic plasticity models like the Drucker-Prager yield criterion instead of inventing new anisotropic plasticity models for every phenomenon we wish to simulate.
Visual Analysis of Missing Values in Longitudinal Cohort Study Data
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Alemzadeh, S.; Niemann, U.; Ittermann, T.; Völzke, H.; Schneider, D.; Spiliopoulou, M.; Bühler, K.; Preim, B.; Benes, Bedrich and Hauser, Helwig
Attrition or dropout is the most severe missingness problem in longitudinal cohort study data where some participants do not show up for follow‐up examinations. Dropouts result in biased data and cause the reduction of 1ata set size. Moreover, they limit the power of statistical analysis and the validity of study findings. Visualization can play a strong role in analysing and displaying the missingness patterns. In this work, we present VIVID, a framework for the isual analysis of mssing alues n cohort study ata. VIVID is inspired by discussions with epidemiologists and adds visual components to their current statistics‐based approaches. VIVID provides functions for exploration, imputation and validity check of imputations. The main focus of this paper is multiple imputation to fix the missing data.
Fast and Scalable Solvers for the Fluid Pressure Equations with Separating Solid Boundary Conditions
(The Eurographics Association and John Wiley & Sons Ltd., 2020) Lai, Junyu; Chen, Yangang; Gu, Yu; Batty, Christopher; Wan, Justin W. L.; Panozzo, Daniele and Assarsson, Ulf
In this paper, we propose and evaluate fast, scalable approaches for solving the linear complementarity problems (LCP) arising from the fluid pressure equations with separating solid boundary conditions. Specifically, we present a policy iteration method, a penalty method, and a modified multigrid method, and demonstrate that each is able to properly handle the desired boundary conditions. Moreover, we compare our proposed methods against existing approaches and show that our solvers are more efficient and exhibit better scaling behavior; that is, the number of iterations required for convergence is essentially independent of grid resolution, and thus they are faster at larger grid resolutions. For example, on a 256 grid our multigrid method was 30 times faster than the prior multigrid method in the literature.
Semi-Supervised 3D Shape Recognition via Multimodal Deep Co-training
(The Eurographics Association and John Wiley & Sons Ltd., 2020) Song, Mofei; Liu, Yu; Liu, Xiao Fan; Eisemann, Elmar and Jacobson, Alec and Zhang, Fang-Lue
3D shape recognition has been actively investigated in the field of computer graphics. With the rapid development of deep learning, various deep models have been introduced and achieved remarkable results. Most 3D shape recognition methods are supervised and learn only from the large amount of labeled shapes. However, it is expensive and time consuming to obtain such a large training set. In contrast to these methods, this paper studies a semi-supervised learning framework to train a deep model for 3D shape recognition by using both labeled and unlabeled shapes. Inspired by the co-training algorithm, our method iterates between model training and pseudo-label generation phases. In the model training phase, we train two deep networks based on the point cloud and multi-view representation simultaneously. In the pseudo-label generation phase, we generate the pseudo-labels of the unlabeled shapes using the joint prediction of two networks, which augments the labeled set for the next iteration. To extract more reliable consensus information from multiple representations, we propose an uncertainty-aware consistency loss function to combine the two networks into a multimodal network. This not only encourages the two networks to give similar predictions on the unlabeled set, but also eliminates the negative influence of the large performance gap between the two networks. Experiments on the benchmark ModelNet40 demonstrate that, with only 10% labeled training data, our approach achieves competitive performance to the results reported by supervised methods.
EUROGRAPHICS 2020: CGF 39-2 Frontmatter
(The Eurographics Association and John Wiley & Sons Ltd., 2020) Assarsson, Ulf; Panozzo, Daniele; Panozzo, Daniele and Assarsson, Ulf
-
Resolving Conflicting Insights in Asynchronous Collaborative Visual Analysis
(The Eurographics Association and John Wiley & Sons Ltd., 2020) Li, Jianping Kelvin; Xu, Shenyu; Ye, Yecong (Chris); Ma, Kwan-Liu; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
Analyzing large and complex datasets for critical decision making can benefit from a collective effort involving a team of analysts. However, insights and findings from different analysts are often incomplete, disconnected, or even conflicting. Most existing analysis tools lack proper support for examining and resolving the conflicts among the findings in order to consolidate the results of collaborative data analysis. In this paper, we present CoVA, a visual analytics system incorporating conflict detection and resolution for supporting asynchronous collaborative data analysis. By using a declarative visualization language and graph representation for managing insights and insight provenance, CoVA effectively leverages distributed revision control workflow from software engineering to automatically detect and properly resolve conflicts in collaborative analysis results. In addition, CoVA provides an effective visual interface for resolving conflicts as well as combining the analysis results. We conduct a user study to evaluate CoVA for collaborative data analysis. The results show that CoVA allows better understanding and use of the findings from different analysts.
Interactive Programming for Parametric CAD
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Mathur, Aman; Pirron, Marcus; Zufferey, Damien; Benes, Bedrich and Hauser, Helwig
Parametric computer‐aided design (CAD) enables description of a family of objects, wherein each valid combination of parameter values results in a different final form. Although Graphical User Interface (GUI)‐based CAD tools are significantly more popular, GUI operations do not carry a semantic description, and are therefore brittle with respect to changes in parameter values. Programmatic interfaces, on the other hand, are more robust due to an exact specification of how the operations are applied. However, programming is unintuitive and has a steep learning curve. In this work, we link the interactivity of GUI with the robustness of programming. Inspired by programme synthesis by example, our technique synthesizes code representative of selections made by users in a GUI interface. Through experiments, we demonstrate that our technique can synthesize relevant and robust sub‐programmes in a reasonable amount of time. A user study reveals that our interface offers significant improvements over a programming‐only interface.
DFR: Differentiable Function Rendering for Learning 3D Generation from Images
(The Eurographics Association and John Wiley & Sons Ltd., 2020) Wu, Yunjie; Sun, Zhengxing; Jacobson, Alec and Huang, Qixing
Learning-based 3D generation is a popular research field in computer graphics. Recently, some works adapted implicit function defined by a neural network to represent 3D objects and have become the current state-of-the-art. However, training the network requires precise ground truth 3D data and heavy pre-processing, which is unrealistic. To tackle this problem, we propose the DFR, a differentiable process for rendering implicit function representation of 3D objects into 2D images. Briefly, our method is to simulate the physical imaging process by casting multiple rays through the image plane to the function space, aggregating all information along with each ray, and performing a differentiable shading according to every ray's state. Some strategies are also proposed to optimize the rendering pipeline, making it efficient both in time and memory to support training a network. With DFR, we can perform many 3D modeling tasks with only 2D supervision. We conduct several experiments for various applications. The quantitative and qualitative evaluations both demonstrate the effectiveness of our method.
Normal‐Based Bas‐Relief Modelling via Near‐Lighting Photometric Stereo
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Wei, M.; Song, Z.; Nie, Y.; Wu, J.; Ji, Z.; Guo, Y.; Xie, H.; Wang, J.; Wang, F. L.; Benes, Bedrich and Hauser, Helwig
We present a ear‐ighting hotometric tereo (NL‐PS) system to produce digital bas‐reliefs from a physical object (set) directly. Unlike both the 2D image and 3D model‐based modelling methods that require complicated interactions and transformations, the technique using NL‐PS is easy to use with cost‐effective hardware, providing users with a trade‐off between abstract and representation when creating bas‐reliefs. Our algorithm consists of two steps: normal map acquisition and constrained 3D reconstruction. First, we introduce a lighting model, named the uasi‐oint ighting odel (QPLM), and provide a two‐step calibration solution in our NL‐PS system to generate a dense normal map. Second, we filter the normal map into a and a , and formulate detail‐ or structure‐preserving bas‐relief modelling as a constrained surface reconstruction problem of solving a sparse linear system. The main contribution is a WYSIWYG (i.e. what you see is what you get) way of building new solvers that produces multi‐style bas‐reliefs with their geometric structures and/or details preserved. The performance of our approach is experimentally validated via comparisons with the state‐of‐the‐art methods.
Topology-Aware Surface Reconstruction for Point Clouds
(The Eurographics Association and John Wiley & Sons Ltd., 2020) Brüel-Gabrielsson, Rickard; Ganapathi-Subramanian, Vignesh; Skraba, Primoz; Guibas, Leonidas J.; Jacobson, Alec and Huang, Qixing
We present an approach to incorporate topological priors in the reconstruction of a surface from a point scan. We base the reconstruction on basis functions which are optimized to provide a good fit to the point scan while satisfying predefined topological constraints. We optimize the parameters of a model to obtain a likelihood function over the reconstruction domain. The topological constraints are captured by persistence diagrams which are incorporated within the optimization algorithm to promote the correct topology. The result is a novel topology-aware technique which can (i) weed out topological noise from point scans, and (ii) capture certain nuanced properties of the underlying shape which could otherwise be lost while performing surface reconstruction. We show results reconstructing shapes with multiple potential topologies, compare to other classical surface construction techniques, and show the completion of real scan data.
Segment Tracing Using Local Lipschitz Bounds
(The Eurographics Association and John Wiley & Sons Ltd., 2020) Galin, Eric; Guérin, Eric; Paris, Axel; Peytavie, Adrien; Panozzo, Daniele and Assarsson, Ulf
We introduce Segment Tracing, a new algorithm that accelerates the classical Sphere Tracing method for computing the intersection between a ray and an implicit surface. Our approach consists in computing the Lipschitz bound locally over a segment to improve the marching step computation and accelerate the overall process. We describe the computation of the Lipschitz bound for different operators and primitives. We demonstrate that our algorithm significantly reduces the number of field function queries compared to previous methods, without the need for additional accelerating data-structures. Our method can be applied to a vast variety of implicit models ranging from hierarchical procedural objects built from complex primitives, to simulation-generated implicit surfaces created from many particles.

Browse

Browsing Volume 39 (2020) by Issue Date

Results Per Page

Sort Options