39-Issue 6

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https://diglib.eg.org/handle/10.2312/2632940

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Accelerating Liquid Simulation With an Improved Data‐Driven Method
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Gao, Yang; Zhang, Quancheng; Li, Shuai; Hao, Aimin; Qin, Hong; Benes, Bedrich and Hauser, Helwig
In physics‐based liquid simulation for graphics applications, pressure projection consumes a significant amount of computational time and is frequently the bottleneck of the computational efficiency. How to rapidly apply the pressure projection and at the same time how to accurately capture the liquid geometry are always among the most popular topics in the current research trend in liquid simulations. In this paper, we incorporate an artificial neural network into the simulation pipeline for handling the tricky projection step for liquid animation. Compared with the previous neural‐network‐based works for gas flows, this paper advocates new advances in the composition of representative features as well as the loss functions in order to facilitate fluid simulation with free‐surface boundary. Specifically, we choose both the velocity and the level‐set function as the additional representation of the fluid states, which allows not only the motion but also the boundary position to be considered in the neural network solver. Meanwhile, we use the divergence error in the loss function to further emulate the lifelike behaviours of liquid. With these arrangements, our method could greatly accelerate the pressure projection step in liquid simulation, while maintaining fairly convincing visual results. Additionally, our neutral network performs well when being applied to new scene synthesis even with varied boundaries or scales.
ZerNet: Convolutional Neural Networks on Arbitrary Surfaces Via Zernike Local Tangent Space Estimation
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Sun, Zhiyu; Rooke, Ethan; Charton, Jerome; He, Yusen; Lu, Jia; Baek, Stephen; Benes, Bedrich and Hauser, Helwig
In this paper, we propose a novel formulation extending convolutional neural networks (CNN) to arbitrary two‐dimensional manifolds using orthogonal basis functions called Zernike polynomials. In many areas, geometric features play a key role in understanding scientific trends and phenomena, where accurate numerical quantification of geometric features is critical. Recently, CNNs have demonstrated a substantial improvement in extracting and codifying geometric features. However, the progress is mostly centred around computer vision and its applications where an inherent grid‐like data representation is naturally present. In contrast, many geometry processing problems deal with curved surfaces and the application of CNNs is not trivial due to the lack of canonical grid‐like representation, the absence of globally consistent orientation and the incompatible local discretizations. In this paper, we show that the Zernike polynomials allow rigourous yet practical mathematical generalization of CNNs to arbitrary surfaces. We prove that the convolution of two functions can be represented as a simple dot product between Zernike coefficients and the rotation of a convolution kernel is essentially a set of 2 × 2 rotation matrices applied to the coefficients. The key contribution of this work is in such a computationally efficient but rigorous generalization of the major CNN building blocks.
ConceptGraph: A Formal Model for Interpretation and Reasoning During Visual Analysis
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Karer, B.; Scheler, I.; Hagen, H.; Leitte, H.; Benes, Bedrich and Hauser, Helwig
In order to discuss the kinds of reasoning a visualization supports and the conclusions that can be drawn within the analysis context, a theoretical framework is needed that enables a formal treatment of the reasoning process. Such a model needs to encompass three stages of the visualization pipeline: encoding, decoding and interpretation. The encoding details how data are transformed into a visualization and what can be seen in the visualization. The decoding explains how humans construct graphical contexts inside the depicted visualization and how they interpret them assigning meaning to displayed structures according to a formal reasoning strategy. In the presented model, we adapt and combine theories for the different steps into a unified formal framework such that the analysis process is modelled as an assignment of meaning to displayed structures according to a formal reasoning strategy. Additionally, we propose the ConceptGraph, a combined graph‐based representation of the finite‐state transducers resulting from the three stages, that can be used to formalize and understand the reasoning process. We apply the new model to several visualization types and investigate reasoning strategies for various tasks.
Guide Me in Analysis: A Framework for Guidance Designers
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Ceneda, Davide; Andrienko, Natalia; Andrienko, Gennady; Gschwandtner, Theresia; Miksch, Silvia; Piccolotto, Nikolaus; Schreck, Tobias; Streit, Marc; Suschnigg, Josef; Tominski, Christian; Benes, Bedrich and Hauser, Helwig
Guidance is an emerging topic in the field of visual analytics. Guidance can support users in pursuing their analytical goals more efficiently and help in making the analysis successful. However, it is not clear how guidance approaches should be designed and what specific factors should be considered for effective support. In this paper, we approach this problem from the perspective of guidance designers. We present a framework comprising requirements and a set of specific phases designers should go through when designing guidance for visual analytics. We relate this process with a set of quality criteria we aim to support with our framework, that are necessary for obtaining a suitable and effective guidance solution. To demonstrate the practical usability of our methodology, we apply our framework to the design of guidance in three analysis scenarios and a design walk‐through session. Moreover, we list the emerging challenges and report how the framework can be used to design guidance solutions that mitigate these issues.
Analysis of Schedule and Layout Tuning for Sparse Matrices With Compound Entries on GPUs
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Mueller‐Roemer, J. S.; Stork, A.; Fellner, D.; Benes, Bedrich and Hauser, Helwig
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 other areas of computer graphics. We generalize several matrix layouts and apply joint schedule and layout autotuning to improve the performance of the sparse matrix‐vector product on massively parallel graphics processing units. Compared to schedule tuning without layout tuning, we achieve speedups of up to 5.5 × . In comparison to cuSPARSE, we achieve speedups of up to 4.7 × .
Curve Skeleton Extraction From 3D Point Clouds Through Hybrid Feature Point Shifting and Clustering
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Hu, Hailong; Li, Zhong; Jin, Xiaogang; Deng, Zhigang; Chen, Minhong; Shen, Yi; Benes, Bedrich and Hauser, Helwig
Curve skeleton is an important shape descriptor with many potential applications in computer graphics, visualization and machine intelligence. We present a curve skeleton expression based on the set of the cross‐section centroids from a point cloud model and propose a corresponding extraction approach. We first provide the substitution of a distance field for a 3D point cloud model, and then combine it with curvatures to capture hybrid feature points. By introducing relevant facets and points, we shift these hybrid feature points along the skeleton‐guided normal directions to approach local centroids, simplify them through a tensor‐based spectral clustering and finally connect them to form a primary connected curve skeleton. Furthermore, we refine the primary skeleton through pruning, trimming and smoothing. We compared our results with several state‐of‐the‐art algorithms including the rotational symmetry axis (ROSA) and ‐medial methods for incomplete point cloud data to evaluate the effectiveness and accuracy of our method.
Exploring the Effects of Aggregation Choices on Untrained Visualization Users' Generalizations From Data
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Nguyen, F.; Qiao, X.; Heer, J.; Hullman, J.; Benes, Bedrich and Hauser, Helwig
Visualization system designers must decide whether and how to aggregate data by default. Aggregating distributional information in a single summary mark like a mean or sum simplifies interpretation, but may lead untrained users to overlook distributional features. We ask, How are the conclusions drawn by untrained visualization users affected by aggregation strategy? We present two controlled experiments comparing generalizations of a population that untrained users made from visualizations that summarized either a 1000 record or 50 record sample with either single mean summary mark, a disaggregated view with one mark per observation or a view overlaying a mean summary mark atop a disaggregated view. While we observe no reliable effect of aggregation strategy on generalization accuracy at either sample size, users of purely disaggregated views were slightly less confident in their generalizations on average than users whose views show a single mean summary mark, and less likely to engage in dichotomous thinking about effects as either present or absent. Comparing results from 1000 record to 50 record data set, we see a considerably larger decrease in the number of generalizations produced and reported confidence in generalizations among viewers who saw disaggregated data relative to those who saw only mean summary marks.
Making Sense of Scientific Simulation Ensembles With Semantic Interaction
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Dahshan, M.; Polys, N. F.; Jayne, R. S.; Pollyea, R. M.; Benes, Bedrich and Hauser, Helwig
In the study of complex physical systems, scientists use simulations to study the effects of different models and parameters. Seeking to understand the influence and relationships among multiple dimensions, they typically run many simulations and vary the initial conditions in what are known as ‘ensembles’. Ensembles are then a number of runs that are each multi‐dimensional and multi‐variate. In order to understand the connections between simulation parameters and patterns in the output data, we have been developing an approach to the visual analysis of scientific data that merges human expertise and intuition with machine learning and statistics. Our approach is manifested in a new visualization tool, GLEE (Graphically‐Linked Ensemble Explorer), that allows scientists to explore, search, filter and make sense of their ensembles. GLEE uses visualization and semantic interaction (SI) techniques to enable scientists to find similarities and differences between runs, find correlation(s) between different parameters and explore relations and correlations across and between different runs and parameters. Our approach supports scientists in selecting interesting subsets of runs in order to investigate and summarize the factors and statistics that show variations and consistencies across different runs. In this paper, we evaluate our tool with experts to understand its strengths and weaknesses for optimization and inverse problems.
Multi‐Level Memory Structures for Simulating and Rendering Smoothed Particle Hydrodynamics
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Winchenbach, R.; Kolb, A.; Benes, Bedrich and Hauser, Helwig
In this paper, we present a novel hash map‐based sparse data structure for Smoothed Particle Hydrodynamics, which allows for efficient neighbourhood queries in spatially adaptive simulations as well as direct ray tracing of fluid surfaces. Neighbourhood queries for adaptive simulations are improved by using multiple independent data structures utilizing the same underlying self‐similar particle ordering, to significantly reduce non‐neighbourhood particle accesses. Direct ray tracing is performed using an auxiliary data structure, with constant memory consumption, which allows for efficient traversal of the hash map‐based data structure as well as efficient intersection tests. Overall, our proposed method significantly improves the performance of spatially adaptive fluid simulations and allows for direct ray tracing of the fluid surface with little memory overhead.
Spherical Gaussian‐based Lightcuts for Glossy Interreflections
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Huo, Y.C.; Jin, S.H.; Liu, T.; Hua, W.; Wang, R.; Bao, H.J.; Benes, Bedrich and Hauser, Helwig
It is still challenging to render directional but non‐specular reflections in complex scenes. The SG‐based (Spherical Gaussian) many‐light framework provides a scalable solution but still requires a large number of glossy virtual lights to avoid spikes as well as reduce clamping errors. Directly gathering contributions from these glossy virtual lights to each pixel in a pairwise way is very inefficient. In this paper, we propose an adaptive algorithm with tighter error bounds to efficiently compute glossy interreflections from glossy virtual lights. This approach is an extension of the Lightcuts that builds hierarchies on both lights and pixels with new error bounds and new GPU‐based traversal methods between light and pixel hierarchies. Results demonstrate that our method is able to faithfully and efficiently compute glossy interreflections in scenes with highly glossy and spatial varying reflectance. Compared with the conventional Lightcuts method, our approach generates lightcuts with only one‐fourth to one‐fifth light nodes therefore exhibits better scalability. Additionally, after being implemented on GPU, our algorithms achieve a magnitude of faster performance than the previous method.
Data‐Driven Facial Simulation
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Romeo, M.; Schvartzman, S. C.; Benes, Bedrich and Hauser, Helwig
In Visual Effects, the creation of realistic facial performances is still a challenge that the industry is trying to overcome. Blendshape deformation is used to reproduce the action of different groups of muscles, which produces realistic static results. However, this is not sufficient to generate believable and detailed facial performances of animated digital characters.To increase the realism of facial performances, it is possible to enhance standard facial rigs using physical simulation approaches. However, setting up a simulation rig and controlling material properties according to the performance is not an easy task and could take a lot of time and iterations to get it right.We present a workflow that allows us to generate an activation map for the fibres of a set of superficial patches we call . The pseudo‐muscles are automatically identified using k‐means to cluster the data from the blendshape targets in the animation rig and compute the direction of their contraction (direction of the pseudo‐muscle fibres). We use an Extended Position–Based Dynamics solver to add physical simulation to the facial animation, controlling the behaviour of simulation through the activation map. We show the results achieved using the proposed solution on two digital humans and one fantastic cartoon character, demonstrating that the identified pseudo‐muscles approximate facial anatomy and the simulation properties are properly controlled, increasing the realism while preserving the work of animators.
Stereo Inverse Brightness Modulation for Guidance in Dynamic Panorama Videos in Virtual Reality
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Grogorick, Steve; Tauscher, Jan‐Philipp; Heesen, Nikkel; Castillo, Susana; Magnor, Marcus; Benes, Bedrich and Hauser, Helwig
The peak of virtual reality offers new exciting possibilities for the creation of media content but also poses new challenges. Some areas of interest might be overlooked because the visual content fills up a large portion of viewers' visual field. Moreover, this content is available in 360° around the viewer, yielding locations completely out of sight, making, for example, recall or storytelling in cinematic Virtual Reality (VR) quite difficult.In this paper, we present an evaluation of Stereo Inverse Brightness Modulation for effective and subtle guidance of participants' attention while navigating dynamic virtual environments. The used technique exploits the binocular rivalry effect from human stereo vision and was previously shown to be effective in static environments. Moreover, we propose an extension of the method for successful guidance towards target locations outside the initial visual field.We conduct three perceptual studies, using 13 distinct panorama videos and two VR systems (a VR head mounted display and a fully immersive dome projection system), to investigate (1) general applicability to dynamic environments, (2) stimulus parameter and VR system influence, and (3) effectiveness of the proposed extension for out‐of‐sight targets. Our results prove the applicability of the method to dynamic environments while maintaining its unobtrusive appearance.
Constructing Human Motion Manifold With Sequential Networks
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Jang, Deok‐Kyeong; Lee, Sung‐Hee; Benes, Bedrich and Hauser, Helwig
This paper presents a novel recurrent neural network‐based method to construct a latent motion manifold that can represent a wide range of human motions in a long sequence. We introduce several new components to increase the spatial and temporal coverage in motion space while retaining the details of motion capture data. These include new regularization terms for the motion manifold, combination of two complementary decoders for predicting joint rotations and joint velocities and the addition of the forward kinematics layer to consider both joint rotation and position errors. In addition, we propose a set of loss terms that improve the overall quality of the motion manifold from various aspects, such as the capability of reconstructing not only the motion but also the latent manifold vector, and the naturalness of the motion through adversarial loss. These components contribute to creating compact and versatile motion manifold that allows for creating new motions by performing random sampling and algebraic operations, such as interpolation and analogy, in the latent motion manifold.
VisualNeuro: A Hypothesis Formation and Reasoning Application for Multi‐Variate Brain Cohort Study Data
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Jönsson, Daniel; Bergström, Albin; Forsell, Camilla; Simon, Rozalyn; Engström, Maria; Walter, Susanna; Ynnerman, Anders; Hotz, Ingrid; Benes, Bedrich and Hauser, Helwig
We present an application, and its development process, for interactive visual analysis of brain imaging data and clinical measurements. The application targets neuroscientists interested in understanding the correlations between active brain regions and physiological or psychological factors. The application has been developed in a participatory design process and has subsequently been released as the free software ‘VisualNeuro’. From initial observations of the neuroscientists' workflow, we concluded that while existing tools provide powerful analysis options, they lack effective interactive exploration requiring the use of many tools side by side. Consequently, our application has been designed to simplify the workflow combining statistical analysis with interactive visual exploration. The resulting environment comprises parallel coordinates for effective overview and selection, Welch's t‐test to filter out brain regions with statistically significant differences and multiple visualizations for comparison between brain regions and clinical parameters. These exploration concepts enable neuroscientists to interactively explore the complex bidirectional interplay between clinical and brain measurements and easily compare different patient groups. A qualitative user study has been performed with three neuroscientists from different domains. The study shows that the developed environment supports simultaneous analysis of more parameters, provides rapid pathways to insights and is an effective tool for hypothesis formation.
Interactive Subsurface Scattering for Materials With High Scattering Distances
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Maisch, Sebastian; Ropinski, Timo; Benes, Bedrich and Hauser, Helwig
Existing algorithms for rendering subsurface scattering in real time cannot deal well with scattering over longer distances. Kernels for image space algorithms become very large in these circumstances and separation does not work anymore, while geometry‐based algorithms cannot preserve details very well. We present a novel approach that deals with all these downsides. While for lower scattering distances, the advantages of geometry‐based methods are small, this is not the case anymore for high scattering distances (as we will show). Our proposed method takes advantage of the highly detailed results of image space algorithms and combines it with a geometry‐based method to add the essential scattering from sources not included in image space. Our algorithm does not require pre‐computation based on the scene's geometry, it can be applied to static and animated objects directly. Our method is able to provide results that come close to ray‐traced images which we will show in direct comparisons with images generated by PBRT. We will compare our results to state of the art techniques that are applicable in these scenarios and will show that we provide superior image quality while maintaining interactive rendering times.
Preserving Shadow Silhouettes in Illumination‐Driven Mesh Reduction
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Bethe, F.; Jendersie, J.; Grosch, T.; Benes, Bedrich and Hauser, Helwig
A main challenge for today's renderers is the ever‐growing size of 3D scenes, exceeding the capacity of typically available main memory. This especially holds true for graphics processing units (GPUs) which could otherwise be used to greatly reduce rendering time. A lot of the memory is spent on detailed geometry with mostly imperceptible influence on the final image, even in a global illumination context. Illumination‐driven mesh reduction, a Monte Carlo–based global illumination simulation, steers its mesh reduction towards areas with low visible contribution. While this works well for preserving high‐energy light paths such as caustics, it does have problems: First, objects casting shadows while not being visible themselves are not preserved, resulting in highly inaccurate shadows. Secondly, non‐transparent objects lack proper reduction guidance since there is no importance gradient on their backside, resulting in visible over‐simplification. We present a solution to these problems by extending illumination‐driven mesh reduction with occluder information, focusing on their silhouettes as well as combining it with commonly used error quadrics to preserve geometric features. Additionally, we demonstrate that the combined algorithm still supports iterative refinement of initially reduced geometry, resulting in an image visually similar to an unreduced rendering and enabling out‐of‐core operation.
A Survey on Visualizations for Musical Data
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Khulusi, R.; Kusnick, J.; Meinecke, C.; Gillmann, C.; Focht, J.; Jänicke, S.; Benes, Bedrich and Hauser, Helwig
Digital methods are increasingly applied to store, structure and analyse vast amounts of musical data. In this context, visualization plays a crucial role, as it assists musicologists and non‐expert users in data analysis and in gaining new knowledge. This survey focuses on this unique link between musicology and visualization. We classify 129 related works according to the visualized data types, and we analyse which visualization techniques were applied for certain research inquiries and to fulfill specific tasks. Next to scientific references, we take commercial music software and public websites into account, that contribute novel concepts of visualizing musicological data. We encounter different aspects of uncertainty as major problems when dealing with musicological data and show how occurring inconsistencies are processed and visually communicated. Drawing from our overview in the field, we identify open challenges for research on the interface of musicology and visualization to be tackled in the future.
A Discriminative Multi‐Channel Facial Shape (MCFS) Representation and Feature Extraction for 3D Human Faces
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Gong, Xun; Li, Xin; Li, Tianrui; Liang, Yongqing; Benes, Bedrich and Hauser, Helwig
Building an effective representation for 3D face geometry is essential for face analysis tasks, that is, landmark detection, face recognition and reconstruction. This paper proposes to use a Multi‐Channel Facial Shape (MCFS) representation that consists of depth, hand‐engineered feature and attention maps to construct a 3D facial descriptor. And, a multi‐channel adjustment mechanism, named filtered squeeze and reversed excitation (FSRE), is proposed to re‐organize MCFS data. To assign a suitable weight for each channel, FSRE is able to learn the importance of each layer automatically in the training phase. MCFS and FSRE blocks collaborate together effectively to build a robust 3D facial shape representation, which has an excellent discriminative ability. Extensive experimental results, testing on both high‐resolution and low‐resolution face datasets, show that facial features extracted by our framework outperform existing methods. This representation is stable against occlusions, data corruptions, expressions and pose variations. Also, unlike traditional methods of 3D face feature extraction, which always take minutes to create 3D features, our system can run in real time.
Physically Based Simulation and Rendering of Urban Thermography
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Aguerre, José Pedro; García‐Nevado, Elena; Acuña Paz y Miño, Jairo; Fernández, Eduardo; Beckers, Benoit; Benes, Bedrich and Hauser, Helwig
Urban thermography is a non‐invasive measurement technique commonly used for building diagnosis and energy efficiency evaluation. The physical interpretation of thermal images is a challenging task because they do not necessarily depict the real temperature of the surfaces, but one estimated from the measured incoming radiation. In this sense, the computational rendering of a thermal image can be useful to understand the results captured in a measurement campaign. The computer graphics community has proposed techniques for light rendering that are used for its thermal counterpart. In this work, a physically based simulation methodology based on a combination of the finite element method (FEM) and ray tracing is presented. The proposed methods were tested using a highly detailed urban geometry. Directional emissivity models, glossy reflectivity functions and importance sampling were used to render thermal images. The simulation results were compared with a set of measured thermograms, showing good agreement between them.
NEVA: Visual Analytics to Identify Fraudulent Networks
(© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) A. Leite, Roger; Gschwandtner, Theresia; Miksch, Silvia; Gstrein, Erich; Kuntner, Johannes; Benes, Bedrich and Hauser, Helwig
Trust‐ability, reputation, security and quality are the main concerns for public and private financial institutions. To detect fraudulent behaviour, several techniques are applied pursuing different goals. For well‐defined problems, analytical methods are applicable to examine the history of customer transactions. However, fraudulent behaviour is constantly changing, which results in ill‐defined problems. Furthermore, analysing the behaviour of individual customers is not sufficient to detect more complex structures such as networks of fraudulent actors. We propose NEVA (Network dEtection with Visual Analytics), a Visual Analytics exploration environment to support the analysis of customer networks in order to reduce false‐negative and false‐positive alarms of frauds. Multiple coordinated views allow for exploring complex relations and dependencies of the data. A guidance‐enriched component for network pattern generation, detection and filtering support exploring and analysing the relationships of nodes on different levels of complexity. In six expert interviews, we illustrate the applicability and usability of NEVA.

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