Volume 37 (2018)
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Item Sensor-aware Normal Estimation for Point Clouds from 3D Range Scans(The Eurographics Association and John Wiley & Sons Ltd., 2018) Comino Trinidad, Marc; Andujar, Carlos; Chica, Antonio; Brunet, Pere; Ju, Tao and Vaxman, AmirNormal vectors are essential for many point cloud operations, including segmentation, reconstruction and rendering. The robust estimation of normal vectors from 3D range scans is a challenging task due to undersampling and noise, specially when combining points sampled from multiple sensor locations. Our error model assumes a Gaussian distribution of the range error with spatially-varying variances that depend on sensor distance and reflected intensity, mimicking the features of Lidar equipment. In this paper we study the impact of measurement errors on the covariance matrices of point neighborhoods. We show that covariance matrices of the true surface points can be estimated from those of the acquired points plus sensordependent directional terms. We derive a lower bound on the neighbourhood size to guarantee that estimated matrix coefficients will be within a predefined error with a prescribed probability. This bound is key for achieving an optimal trade-off between smoothness and fine detail preservation. We also propose and compare different strategies for handling neighborhoods with samples coming from multiple materials and sensors. We show analytically that our method provides better normal estimates than competing approaches in noise conditions similar to those found in Lidar equipment.Item Interactive Analysis of Word Vector Embeddings(The Eurographics Association and John Wiley & Sons Ltd., 2018) Heimerl, Florian; Gleicher, Michael; Jeffrey Heer and Heike Leitte and Timo RopinskiWord vector embeddings are an emerging tool for natural language processing. They have proven beneficial for a wide variety of language processing tasks. Their utility stems from the ability to encode word relationships within the vector space. Applications range from components in natural language processing systems to tools for linguistic analysis in the study of language and literature. In many of these applications, interpreting embeddings and understanding the encoded grammatical and semantic relations between words is useful, but challenging. Visualization can aid in such interpretation of embeddings. In this paper, we examine the role for visualization in working with word vector embeddings. We provide a literature survey to catalogue the range of tasks where the embeddings are employed across a broad range of applications. Based on this survey, we identify key tasks and their characteristics. Then, we present visual interactive designs that address many of these tasks. The designs integrate into an exploration and analysis environment for embeddings. Finally, we provide example use cases for them and discuss domain user feedback.Item A Survey of Surface‐Based Illustrative Rendering for Visualization(© 2018 The Eurographics Association and John Wiley & Sons Ltd., 2018) Lawonn, Kai; Viola, Ivan; Preim, Bernhard; Isenberg, Tobias; Chen, Min and Benes, BedrichIn this paper, we survey illustrative rendering techniques for 3D surface models. We first discuss the field of illustrative visualization in general and provide a new definition for this sub‐area of visualization. For the remainder of the survey, we then focus on surface‐based models. We start by briefly summarizing the differential geometry fundamental to many approaches and discuss additional general requirements for the underlying models and the methods' implementations. We then provide an overview of low‐level illustrative rendering techniques including sparse lines, stippling and hatching, and illustrative shading, connecting each of them to practical examples of visualization applications. We also mention evaluation approaches and list various application fields, before we close with a discussion of the state of the art and future work.In this paper, we survey illustrative rendering techniques for 3D surface models. We first discuss the field of illustrative visualization in general and provide a new definition for this sub‐area of visualization. For the remainder of the survey, we then focus on surface‐based models. We start by briefly summarizing the differential geometry fundamental to many approaches and discuss additional general requirements for the underlying models and the methods' implementations. We then provide an overview of low‐level illustrative rendering techniques including sparse lines, stippling and hatching, and illustrative shading, connecting each of them to practical examples of visualization applications. We also mention evaluation approaches and list various application fields, before we close with a discussion of the state of the art and future work.Item Exploring the Visualization Design Space with Repertory Grids(The Eurographics Association and John Wiley & Sons Ltd., 2018) Kurzhals, Kuno; Weiskopf, Daniel; Jeffrey Heer and Heike Leitte and Timo RopinskiThere is an ongoing discussion in the visualization community about the relevant factors that render a visualization effective, expressive, memorable, aesthetically pleasing, etc. These factors lead to a large design space for visualizations. To explore this design space, qualitative research methods based on observations and interviews are often necessary. We describe an interview method that allows us to systematically acquire and assess important factors from subjective answers by interviewees. To this end, we adopt the repertory grid methodology in the context of visualization. It is based on the personal construct theory: each personality interprets a topic based on a set of personal, basic constructs expressed as contrasts. For the individual interpretation of visualizations, this means that these personal terms can be very different, depending on numerous influences, such as the prior experiences of the interviewed person. We present an interviewing process, visual interface, and qualitative and quantitative analysis procedures that are specifically devised to fit the needs of visualization applications. A showcase interview with 15 typical static information visualizations and 10 participants demonstrates that our approach is effective in identifying common constructs as well as individual differences. In particular, we investigate differences between expert and nonexpert interviewees. Finally, we discuss the differences to other qualitative methods and how the repertory grid can be embedded in existing theoretical frameworks of visualization research for the design process.Item MPM Simulation of Interacting Fluids and Solids(The Eurographics Association and John Wiley & Sons Ltd., 2018) Yan, Xiao; Li, Chen-Feng; Chen, Xiao-Song; Hu, Shi-Min; Thuerey, Nils and Beeler, ThaboThe material point method (MPM) has attracted increasing attention from the graphics community, as it combines the strengths of both particle- and grid-based solvers. Like the smoothed particle hydrodynamics (SPH) scheme, MPM uses particles to discretize the simulation domain and represent the fundamental unknowns. This makes it insensitive to geometric and topological changes, and readily parallelizable on a GPU. Like grid-based solvers, MPM uses a background mesh for calculating spatial derivatives, providing more accurate and more stable results than a purely particle-based scheme. MPM has been very successful in simulating both fluid flow and solid deformation, but less so in dealing with multiple fluids and solids, where the dynamic fluid-solid interaction poses a major challenge. To address this shortcoming of MPM, we propose a new set of mathematical and computational schemes which enable efficient and robust fluid-solid interaction within the MPM framework. These versatile schemes support simulation of both multiphase flow and fully-coupled solid-fluid systems. A series of examples is presented to demonstrate their capabilities and performance in the presence of various interacting fluids and solids, including multiphase flow, fluid-solid interaction, and dissolution.Item PointProNets: Consolidation of Point Clouds with Convolutional Neural Networks(The Eurographics Association and John Wiley & Sons Ltd., 2018) Roveri, Riccardo; Öztireli, A. Cengiz; Pandele, Ioana; Gross, Markus; Gutierrez, Diego and Sheffer, AllaWith the widespread use of 3D acquisition devices, there is an increasing need of consolidating captured noisy and sparse point cloud data for accurate representation of the underlying structures. There are numerous algorithms that rely on a variety of assumptions such as local smoothness to tackle this ill-posed problem. However, such priors lead to loss of important features and geometric detail. Instead, we propose a novel data-driven approach for point cloud consolidation via a convolutional neural network based technique. Our method takes a sparse and noisy point cloud as input, and produces a dense point cloud accurately representing the underlying surface by resolving ambiguities in geometry. The resulting point set can then be used to reconstruct accurate manifold surfaces and estimate surface properties. To achieve this, we propose a generative neural network architecture that can input and output point clouds, unlocking a powerful set of tools from the deep learning literature. We use this architecture to apply convolutional neural networks to local patches of geometry for high quality and efficient point cloud consolidation. This results in significantly more accurate surfaces, as we illustrate with a diversity of examples and comparisons to the state-of-the-art.Item Self-similarity Analysis for Motion Capture Cleaning(The Eurographics Association and John Wiley & Sons Ltd., 2018) Aristidou, Andreas; Cohen-Or, Daniel; Hodgins, Jessica K.; Shamir, Ariel; Gutierrez, Diego and Sheffer, AllaMotion capture sequences may contain erroneous data, especially when the motion is complex or performers are interacting closely and occlusions are frequent. Common practice is to have specialists visually detect the abnormalities and fix them manually. In this paper, we present a method to automatically analyze and fix motion capture sequences by using self-similarity analysis. The premise of this work is that human motion data has a high-degree of self-similarity. Therefore, given enough motion data, erroneous motions are distinct when compared to other motions. We utilize motion-words that consist of short sequences of transformations of groups of joints around a given motion frame. We search for the K-nearest neighbors (KNN) set of each word using dynamic time warping and use it to detect and fix erroneous motions automatically. We demonstrate the effectiveness of our method in various examples, and evaluate by comparing to alternative methods and to manual cleaning.Item Deep Video Stabilization Using Adversarial Networks(The Eurographics Association and John Wiley & Sons Ltd., 2018) Xu, Sen-Zhe; Hu, Jun; Wang, Miao; Mu, Tai-Jiang; Hu, Shi-Min; Fu, Hongbo and Ghosh, Abhijeet and Kopf, JohannesVideo stabilization is necessary for many hand-held shot videos. In the past decades, although various video stabilization methods were proposed based on the smoothing of 2D, 2.5D or 3D camera paths, hardly have there been any deep learning methods to solve this problem. Instead of explicitly estimating and smoothing the camera path, we present a novel online deep learning framework to learn the stabilization transformation for each unsteady frame, given historical steady frames. Our network is composed of a generative network with spatial transformer networks embedded in different layers, and generates a stable frame for the incoming unstable frame by computing an appropriate affine transformation. We also introduce an adversarial network to determine the stability of a piece of video. The network is trained directly using the pair of steady and unsteady videos. Experiments show that our method can produce similar results as traditional methods, moreover, it is capable of handling challenging unsteady video of low quality, where traditional methods fail, such as video with heavy noise or multiple exposures. Our method runs in real time, which is much faster than traditional methods.Item Statistical Modeling of the 3D Geometry and Topology of Botanical Trees(The Eurographics Association and John Wiley & Sons Ltd., 2018) Wang, Guan; Laga, Hamid; Jia, Jinyuan; Xie, Ning; Tabia, Hedi; Ju, Tao and Vaxman, AmirWe propose a framework for statistical modeling of the 3D geometry and topology of botanical trees. We treat botanical trees as points in a tree-shape space equipped with a proper metric that captures the geometric and the topological differences between trees. Geodesics in the tree-shape space correspond to the optimal sequence of deformations, i.e. bending, stretching, and topological changes, which align one tree onto another. In this way, the 3D tree modeling and synthesis problem becomes a problem of exploring the tree-shape space either in a controlled fashion, using statistical regression, or randomly by sampling from probability distributions fitted to populations in the tree-shape space. We show how to use this framework for (1) computing statistical summaries, e.g. the mean and modes of variations, of a population of botanical trees, (2) synthesizing random instances of botanical trees from probability distributions fitted to a population of botanical trees, and (3) modeling, interactively, 3D botanical trees using a simple sketching interface. The approach is fast and only requires as input 3D botanical tree models with a known upright orientation.Item Visual and Quantitative Analysis of Great Arteries' Blood Flow Jets in Cardiac 4D PC-MRI Data(The Eurographics Association and John Wiley & Sons Ltd., 2018) Köhler, Benjamin; Grothoff, Matthias; Gutberlet, Matthias; Preim, Bernhard; Jeffrey Heer and Heike Leitte and Timo RopinskiFlow in the great arteries (aorta, pulmonary artery) is normally laminar with a parabolic velocity profile. Eccentric flow jets are linked to various diseases like aneurysms. Cardiac 4D PC-MRI data provide spatio-temporally resolved blood flow information for the whole cardiac cycle. In this work, we establish a time-dependent visualization and quantification of flow jets. For this purpose, equidistant measuring planes are automatically placed along the vessel's centerline. The flow jet position and region with highest velocities are extracted for every plane in each time step. This is done during pre-processing and without user-defined parameters. We visualize the main flow jet as geometric tube. High-velocity areas are depicted as a net around this tube. Both geometries are time-dependent and can be animated. Quantitative values are provided during cross-sectional measuring plane-based evaluation. Moreover, we offer a plot visualization as summary of flow jet characteristics for the selected plane. Our physiologically plausible results are in accordance with medical findings. Our clinical collaborators appreciate the possibility to view the flow jet in the whole vessel at once, which normally requires repeated pathline filtering due to varying velocities along the vessel course. The overview plots are considered as valuable for documentation purposes.Item Landscaper: A Modeling System for 3D Printing Scale Models of Landscapes(The Eurographics Association and John Wiley & Sons Ltd., 2018) Allahverdi, Kamyar; Djavaherpour, Hessam; Mahdavi-Amiri, Ali; Samavati, Faramarz; Jeffrey Heer and Heike Leitte and Timo RopinskiLandscape models of geospatial regions provide an intuitive mechanism for exploring complex geospatial information. However, the methods currently used to create these scale models require a large amount of resources, which restricts the availability of these models to a limited number of popular public places, such as museums and airports. In this paper, we have proposed a system for creating these physical models using an affordable 3D printer in order to make the creation of these models more widely accessible. Our system retrieves GIS relevant to creating a physical model of a geospatial region and then addresses the two major limitations of affordable 3D printers, namely the limited number of materials and available printing volume. This is accomplished by separating features into distinct extruded layers and splitting large models into smaller pieces, allowing us to employ different methods for the visualization of different geospatial features, like vegetation and residential areas, in a 3D printing context. We confirm the functionality of our system by printing two large physical models of relatively complex landscape regions.Item Single-image Tomography: 3D Volumes from 2D Cranial X-Rays(The Eurographics Association and John Wiley & Sons Ltd., 2018) Henzler, Philipp; Rasche, Volker; Ropinski, Timo; Ritschel, Tobias; Gutierrez, Diego and Sheffer, AllaAs many different 3D volumes could produce the same 2D x-ray image, inverting this process is challenging. We show that recent deep learning-based convolutional neural networks can solve this task. As the main challenge in learning is the sheer amount of data created when extending the 2D image into a 3D volume, we suggest firstly to learn a coarse, fixed-resolution volume which is then fused in a second step with the input x-ray into a high-resolution volume. To train and validate our approach we introduce a new dataset that comprises of close to half a million computer-simulated 2D x-ray images of 3D volumes scanned from 175 mammalian species. Future applications of our approach include stereoscopic rendering of legacy x-ray images, re-rendering of x-rays including changes of illumination, view pose or geometry. Our evaluation includes comparison to previous tomography work, previous learning methods using our data, a user study and application to a set of real x-rays.Item A Visualization Framework and User Studies for Overloaded Orthogonal Drawings(© 2018 The Eurographics Association and John Wiley & Sons Ltd., 2018) Didimo, Walter; Kornaropoulos, Evgenios M.; Montecchiani, Fabrizio; Tollis, Ioannis G.; Chen, Min and Benes, BedrichOverloaded orthogonal drawing (OOD) is a recent graph visualization style specifically conceived for directed graphs. It merges the advantages of some popular drawing conventions like layered drawings and orthogonal drawings, and provides additional support for some common analysis tasks. We present a visualization framework called , which implements algorithms and graphical features for the OOD style. Besides the algorithm for acyclic digraphs, the DAGView framework implements extensions to visualize both digraphs with cycles and undirected graphs, with the additional possibility of taking into account user preferences and constraints. It also supports an interactive visualization of clustered digraphs, based on the use of strongly connected components. Moreover, we describe an experimental user study, aimed to investigate the usability of OOD within the DAGView framework. The results of our study suggest that OOD can be effectively exploited to perform some basic tasks of analysis in a faster and more accurate way when compared to other drawing styles for directed graphs.Overloaded orthogonal drawing (OOD) is a recent graph visualization style specifically conceived for directed graphs. It merges the advantages of some popular drawing conventions like layered drawings and orthogonal drawings, and provides additional support for some common analysis tasks. We present a visualization framework called , which implements algorithms and graphical features for the OOD style. Besides the algorithm for acyclic digraphs, the DAGView framework implements extensions to visualize both digraphs with cycles and undirected graphs, with the additional possibility of taking into account user preferences and constraints.Item Example-based Authoring of Procedural Modeling Programs with Structural and Continuous Variability(The Eurographics Association and John Wiley & Sons Ltd., 2018) Ritchie, Daniel; Jobalia, Sarah; Thomas, Anna; Gutierrez, Diego and Sheffer, AllaProcedural models are a powerful tool for quickly creating a variety of computer graphics content. However, authoring them is challenging, requiring both programming and artistic expertise. In this paper, we present a method for learning procedural models from a small number of example objects. We focus on the modular design setting, where objects are constructed from a common library of parts. Our procedural representation is a probabilistic program that models both the discrete, hierarchical structure of the examples as well as the continuous variability in their spatial arrangements of parts. We develop an algorithm for learning such programs from examples, using combinatorial search over program structures and variational inference to estimate continuous program parameters. We evaluate our method by demonstrating its ability to learn programs from examples of ornamental designs, spaceships, space stations, and castles. Experiments suggest that our learned programs can reliably generate a variety of new objects that are perceptually indistinguishable from hand-crafted examples.Item Curvature Continuity Conditions Between Adjacent Toric Surface Patches(The Eurographics Association and John Wiley & Sons Ltd., 2018) Sun, Lanyin; Zhu, Chungang; Fu, Hongbo and Ghosh, Abhijeet and Kopf, JohannesToric surface patch is the multi-sided generalization of classical Bézier surface patch. Geometric continuity of the parametric surface patches plays a crucial role in geometric modeling. In this paper, the necessary and sufficient conditions of curvature continuity between toric surface patches are illustrated with the theory of toric degeneration. Furthermore, some practical sufficient conditions of curvature continuity of toric surface patches are also developed.Item Human Factors in Streaming Data Analysis: Challenges and Opportunities for Information Visualization(© 2018 The Eurographics Association and John Wiley & Sons Ltd., 2018) Dasgupta, Aritra; Arendt, Dustin L.; Franklin, Lyndsey R.; Wong, Pak Chung; Cook, Kristin A.; Chen, Min and Benes, BedrichReal‐world systems change continuously. In domains such as traffic monitoring or cyber security, such changes occur within short time scales. This results in a streaming data problem and leads to unique challenges for the human in the loop, as analysts have to ingest and make sense of dynamic patterns in real time. While visualizations are being increasingly used by analysts to derive insights from streaming data, we lack a thorough characterization of the human‐centred design problems and a critical analysis of the state‐of‐the‐art solutions that exist for addressing these problems. In this paper, our goal is to fill this gap by studying how the state of the art in streaming data visualization handles the challenges and reflect on the gaps and opportunities. To this end, we have three contributions in this paper: (i) problem characterization for identifying domain‐specific goals and challenges for handling streaming data, (ii) a survey and analysis of the state of the art in streaming data visualization research with a focus on how visualization design meets challenges specific to change perception and (iii) reflections on the design trade‐offs, and an outline of potential research directions for addressing the gaps in the state of the art.Real‐world systems change continuously. In domains such as traffic monitoring or cyber security, such changes occur within short time scales. This results in a streaming data problem and leads to unique challenges for the human in the loop, as analysts have to ingest and make sense of dynamic patterns in real time. While visualizations are being increasingly used by analysts to derive insights from streaming data, we lack a thorough characterization of the human‐centred design problems and a critical analysis of the state‐of‐the‐art solutions that exist for addressing these problems.Item Temporally Consistent Motion Segmentation From RGB‐D Video(© 2018 The Eurographics Association and John Wiley & Sons Ltd., 2018) Bertholet, P.; Ichim, A.E.; Zwicker, M.; Chen, Min and Benes, BedrichTemporally consistent motion segmentation from RGB‐D videos is challenging because of the limitations of current RGB‐D sensors. We formulate segmentation as a motion assignment problem, where a motion is a sequence of rigid transformations through all frames of the input. We capture the quality of each potential assignment by defining an appropriate energy function that accounts for occlusions and a sensor‐specific noise model. To make energy minimization tractable, we work with a discrete set instead of the continuous, high dimensional space of motions, where the discrete motion set provides an upper bound for the original energy. We repeatedly minimize our energy, and in each step extend and refine the motion set to further lower the bound. A quantitative comparison to the current state of the art demonstrates the benefits of our approach in difficult scenarios.Temporally consistent motion segmentation from RGB‐D videos is challenging because of the limitations of current RGB‐D sensors. We formulate segmentation as a motion assignment problem, where a motion is a sequence of rigid transformations through all frames of the input. We capture the quality of each potential assignment by defining an appropriate energy function that accounts for occlusions and a sensor‐specific noise model. To make energy minimization tractable, we work with a discrete set instead of the continuous, high dimensional space of motions, where the discrete motion set provides an upper bound for the original energy. We repeatedly minimize our energy, and in each step extend and refine the motion set to further lower the bound. A quantitative comparison to the current state of the art demonstrates the benefits of our approach in difficult scenarios.Item String Art: Towards Computational Fabrication of String Images(The Eurographics Association and John Wiley & Sons Ltd., 2018) Birsak, Michael; Rist, Florian; Wonka, Peter; Musialski, Przemyslaw; Gutierrez, Diego and Sheffer, AllaIn this paper we propose a novel method for the automatic computation and digital fabrication of artistic string images. String art is a technique used by artists for the creation of abstracted images which are composed of straight lines of strings tensioned between pins distributed on a frame. Together the strings fuse to a perceptible image. Traditionally, artists craft such images manually in a highly sophisticated and tedious design process. To achieve this goal fully automatically we propose a computational setup driven by a discrete optimization algorithm which takes an ordinary picture as input and converts it into a connected graph of strings that tries to reassemble the input image best possibly. Furthermore, we propose a hardware setup for automatic digital fabrication of these images using an industrial robot that spans the strings. Finally, we demonstrate the applicability of our approach by generating and fabricating a set of real string art images.Item FashionGAN: Display your fashion design using Conditional Generative Adversarial Nets(The Eurographics Association and John Wiley & Sons Ltd., 2018) Cui, Yi Rui; Liu, Qi; Gao, Cheng Ying; Su, Zhuo; Fu, Hongbo and Ghosh, Abhijeet and Kopf, JohannesVirtual garment display plays an important role in fashion design for it can directly show the design effect of the garment without having to make a sample garment like traditional clothing industry. In this paper, we propose an end-to-end virtual garment display method based on Conditional Generative Adversarial Networks. Different from existing 3D virtual garment methods which need complex interactions and domain-specific user knowledge, our method only need users to input a desired fashion sketch and a specified fabric image then the image of the virtual garment whose shape and texture are consistent with the input fashion sketch and fabric image can be shown out quickly and automatically. Moreover, it can also be extended to contour images and garment images, which further improves the reuse rate of fashion design. Compared with the existing image-to-image methods, the quality of images generated by our method is better in terms of color and shape.Item Explorative Blood Flow Visualization using Dynamic Line Filtering based on Surface Features(The Eurographics Association and John Wiley & Sons Ltd., 2018) Behrendt, Benjamin; Berg, Philipp; Beuing, Oliver; Preim, Bernhard; Saalfeld, Sylvia; Jeffrey Heer and Heike Leitte and Timo RopinskiRupture risk assessment is a key to devise patient-specific treatment plans of cerebral aneurysms. To understand and predict the development of aneurysms and other vascular diseases over time, both hemodynamic flow patterns and their effect on the vessel surface need to be analyzed. Flow structures close to the vessel wall often correlate directly with local changes in surface parameters, such as pressure or wall shear stress. Yet, in many existing applications, the analyses of flow and surface features are either somewhat detached from one another or only globally available. Especially for the identification of specific blood flow characteristics that cause local startling parameters on the vessel surface, like elevated pressure values, an interactive analysis tool is missing. The explorative visualization of flow data is challenging due to the complexity of the underlying data. In order to find meaningful structures in the entirety of the flow, the data has to be filtered based on the respective explorative aim. In this paper, we present a combination of visualization, filtering and interaction techniques for explorative analysis of blood flow with a focus on the relation of local surface parameters and underlying flow structures. Coherent bundles of pathlines can be interactively selected based on their relation to features of the vessel wall and further refined based on their own hemodynamic features. This allows the user to interactively select and explore flow structures locally affecting a certain region on the vessel wall and therefore to understand the cause and effect relationship between these entities. Additionally, multiple selected flow structures can be compared with respect to their quantitative parameters, such as flow speed. We confirmed the usefulness of our approach by conducting an informal interview with two expert neuroradiologists and an expert in flow simulation. In addition, we recorded several insights the neuroradiologists were able to gain with the help of our tool.