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On-Tube Attribute visualization for Multivariate Trajectory Data

IEEE Transactions on visualization and computer graphics 2023年第1期29卷 1288-1298页

作者： Russig, Benjamin Grab, David Dachselt, Raimund Gumhold, Stefan Department of Computer Graphics and Visualization TU Dresden Germany TU Dresden Interactive Media Lab Germany

Stylized tubes are an established visualization primitive for line data as encountered in many scientific fields, ranging from characteristic lines in flow fields, fiber tracks reconstructed from diffusion tensor imaging, to trajectories of moving objects as they arise from cyber-physical systems in many engineering disciplines. Typical challenges include large data set sizes demanding for efficient rendering techniques as well as a large number of attributes that cannot be mapped simultaneously to the basic visual attributes provided by a tube-based visualization. In this work, we tackle both challenges with a new on-tube visualization approach. We improve recent work on high-quality GPU ray casting of Hermite spline tubes supporting ambient occlusion and extend it by a new layered procedural texturing technique. In the proposed framework, a large number of data set attributes can be mapped simultaneously to a variety of glyphs and plots that are embedded in texture space and organized in layers. Efficient rendering with minimal data transfer is achieved by generating the glyphs procedurally and drawing them in a deferred shading pass. We integrated these techniques in a prototype visualization tool that facilitates flexible mapping of data set attributes to visual tube and glyph attributes. We studied our approach on a variety of example data from different fields and found it to provide a highly adaptable and extensible toolbox to quickly craft tailor-made tube-based trajectory visualizations. © 2022 IEEE.

关键词： Trajectories

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An Immersive Method for Extracting Structural Information from Unorganized Point Clouds

An Immersive Method for Extracting Structural Information fr...

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Nicograph International (NicoInt)

作者： Zhongyuan Yu Tianfang Lin Stefan Gumhold Matthew McGinity Immersive Experience Lab TU Dresden Chair of Computer Graphics and Visualization TU Dresden

ISBN: (数字)9798350386882

ISBN: (纸本)9798350386899

Point clouds find extensive applications across diverse domains such as construction, architecture, and archaeology due to their capacity to encapsulate rich datasets. Given the density and detail of these datasets, extracting accurate structural information (geometrical and connectivity information) demands sophisticated algorithms and tools. The recent advancements in virtual reality (VR) technology and rendering techniques have significantly elevated the ability to visualize these point cloud datasets, affording users an immersive experience within the data. This immersive capability holds the potential to streamline the process of extracting valuable information from these datasets. In this work, we explore the feasibility of extracting and visualizing structural information from point clouds with immersive interfaces. We propose strategies to enhance human perception of the underlying structure and interactive methods to extract face, edge, vertex, and connectivity data from the raw, unorganized point clouds. Our method is evaluated based on public datasets. We believe our work represents a promising attempt to integrate human insights into the data processing pipeline.

关键词： Point cloud compression Geometry Pipelines Data visualization Prototypes Immersive experience Rendering (computer graphics)

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A Constructivism-based Approach to Treemap Literacy in the Classroom

A Constructivism-based Approach to Treemap Literacy in the C...

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44th Annual Conference on European Association for computer graphics, EUROgraphics 2023

作者： Firat, Elif E. Lang, Colm Srinivas, Bhumika Peng, Ilena Laramee, Robert S. Joshi, Alark Department of Computer Engineering Cukurova University Turkey Visualization and Graphics Lab Department of Computer Science University of San Francisco CA United States School of Computer Science University of Nottingham United Kingdom

ISBN: (纸本)9783038682103

Treemaps are a popular representation to show hierarchical as well as part-to-whole relationships in data. While most students are aware of node-link representations/network diagrams based on their K-12 education, treemaps are often a novel representation to them. We present our experience of developing a software using principles from constructivism to help students understand treemaps using linked, side-by-side views of a node-link diagram and a treemap of the same data. Based on the qualitative survey conducted at the end of the intervention, students found the linked views to be beneficial for understanding hierarchical representation of data using treemaps. © 2023 The Authors.

关键词： Students

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Stereo Conversion with Disparity-Aware Warping, Compositing and Inpainting

Stereo Conversion with Disparity-Aware Warping, Compositing ...

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IEEE Workshop on Applications of computer Vision (WACV)

作者： Lukas Mehl Andrés Bruhn Markus Gross Christopher Schroers Institute for Visualization and Interactive Systems University of Stuttgart Department of Computer Science Computer Graphics Lab ETH Zurich DisneyResearch|Studios Switzerland

Despite of exciting advances in image-based rendering and novel view synthesis, it is still challenging to achieve high-resolution results that can reach production-level quality when applying such methods to the task of stereo conversion. At the same time, only very few dedicated stereo conversion approaches exist, which also fall short in terms of the required quality. Hence, in this paper, we present a novel method for high-resolution 2D-to-3D conversion. It is fully differentiable in all of its stages and performs disparity-informed warping, consistent foreground-background compositing, and background-aware inpainting. To enable temporal consistency in the resulting video, we propose a strategy to integrate information from additional video frames. Extensive ablation studies validate our design choices, leading to a fully automatic model that outperforms existing approaches by a large margin (49-70% LPIPS error reduction). Finally, inspired from current practices in manual stereo conversion, we introduce optional interactive tools into our model, which allow to steer the conversion process and make it significantly more applicable for 3D film production.

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A Research Platform for Studying Mixed-Presence Collaboration

A Research Platform for Studying Mixed-Presence Collaboratio...

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IEEE International Symposium on Mixed and Augmented Reality Workshops (ISMARW)

作者： Wolfgang Büschel Katja Krug Marc Satkowski Stefan Gumhold Raimund Dachselt Interactive Media Lab Dresden TUD Dresden University of Technology Chair of Computer Graphics and Visualization TUD Dresden University of Technology

ISBN: (数字)9798331506919

ISBN: (纸本)9798331506926

In this paper, we present a research platform to support studying collaboration in hybrid and co-located scenarios. Mixed-presence collaboration includes various novel and exciting use cases, such as situated and immersive data analysis by multiple users. However, research in this emerging field is hindered by the technical complexity of the setups and often requires re-implementation of common features. We address this issue by contributing a toolkit and research platform for mixed-presence collaboration that serves as an extensible baseline implementation and enables fast prototyping for user studies in collaborative mixed reality. Furthermore, our platform provides adjustable parameters, such as types of avatars, audio source placement, or the amount of simulated network latency. This way, developers are supported in making design choices regarding typical, re-occurring technical challenges.

关键词： Three-dimensional displays Data analysis Avatars Spatial audio Decision making Collaboration Mixed reality Complexity theory Synchronization Augmented reality

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Understanding multi-modal brain network data: An immersive 3D visualization approach

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computers and graphics (Pergamon) 2022年 106卷 88-97页

作者： Pester, Britta Russig, Benjamin Winke, Oliver Ligges, Carolin Dachselt, Raimund Gumhold, Stefan Chair for Computer Graphics and Visualization TU Dresden Germany Jena University Hospital Department of Child and Adolescent Psychiatry Psychosomatic Medicine and Psychotherapy Friedrich Schiller University Jena Germany Interactive Media Lab Dresden TU Dresden Germany TU Dresden Germany Germany

Understanding the human brain requires the incorporation of functional interaction patterns that depend on a variety of features like experimental setup, strength of directed connectedness or variability between several individuals or groups. In addition to these external factors, there are internal properties of the brain network as for example temporal propagation of connections, or connectivity patterns that only occur in a distinct frequency range of the signal. The visualization of detected networks covering all necessary information poses a substantial problem which is mainly due to the high number of features that have to be integrated within the same view in a natural spatial context. To address this problem, we propose a new tool that transfers the network into an anatomically arranged origin–destination view in a virtual visual analysis lab. This offers the user an opportunity to assess the temporal evolution of connectivity patterns and provides an intuitive and motivating way of exploring the corresponding features via navigation and interaction in virtual reality (VR). The approach was evaluated in a user study including participants with neuroscientific background as well as people working in the field of computer science. As a first proof of concept trial we used functional brain networks derived from time series of electroencephalography recordings evoked by visual stimuli. All participants gave a positive general feedback, notably they saw a benefit in using the VR view instead of the compared 2D desktop variant. This suggests that our application successfully fills a gap in the visualization of high-dimensional brain networks and that it is worthwhile to further follow and enhance the proposed representation method. © 2022 Elsevier Ltd

关键词： Electroencephalography

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To the Point: From Dynamic Heatmap Video to Gaze Points 25

To the Point: From Dynamic Heatmap Video to Gaze Points

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Proceedings of the 2025 Symposium on Eye Tracking Research and Applications

作者： Beryl Gnanaraj Swetha Manivasagam Jaya Sreevalsan-Nair Graphics-Visualization-Computing Lab International Institute of Information Technology Bangalore Bangalore Karnataka India Department of Computer Science and Engineering PSG College of Technology Coimbatore Tamil Nadu India

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Improving Uncertainty-Error Correspondence in Deep Bayesian Medical Image Segmentation

TechRxiv

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TechRxiv 2023年

作者： Mody, Prerak de Plaza, Nicolas Chaves Astrenidou, Eleftheria de Ridder, Mischa Hoekstra, Nienke Hildebrandt, Klaus Staring, Marius Radiology Leiden University Medical Center Netherlands The Department of Radiation Oncology Leiden University Medical Center Netherlands University Medical Center Utrecht Netherlands The Computer Graphics and Visualization Lab TU Delft Netherlands

Increased usage of automated tools like deep learning in medical image segmentation has alleviated the bottleneck of manual contouring. This has shifted manual labour to quality assessment (QA) of automated contours which involves detecting errors and correcting them. A potential solution to semi-automated QA is to use deep Bayesian uncertainty to recommend potentially erroneous regions, thus reducing time spent on error detection. Previous work has investigated the correspondence between uncertainty and error, however, no work has been done on improving the "utility" of Bayesian uncertainty maps such that it is only present in inaccurate regions and not in the accurate ones. Our work trains the FlipOut model with the Accuracy-vs-Uncertainty (AvU) loss which promotes uncertainty to be present only in inaccurate regions. We apply this method on datasets of two radiotherapy body sites, namely CT scans of head and neck and prostate MRs. Uncertainty heatmaps (i.e. predictive entropy) are evaluated using ROC and Precision-Recall curves. Numerical results show that when compared to the Bayesian baseline the proposed method successfully suppresses uncertainty for accurate voxels, with similar presence of uncertainty for inaccurate voxels. Code to reproduce experiments is available on https://***/prerakmody/ bayesuncertainty-error-correspondence. © 2023, CC BY.

关键词： computerized tomography

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PREVIS - A Combined Machine Learning and Visual Interpolation Approach for Interactive Reverse Engineering in Assembly Quality Control 15

PREVIS - A Combined Machine Learning and Visual Interpolatio...

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15th CIRP Conference on Intelligent Computation in Manufacturing Engineering, ICME 2021

作者： Ruediger, Patrick Claus, Felix Leonhardt, Viktor Hagen, Hans Aurich, Jan C. Garth, Christoph Technische Universität Kaiserslautern P. O. Box 3049 Kaiserslautern67653 Germany Computer Graphics and HCI Lab Technische Universität Kaiserslautern P. O. Box 3049 Kaiserslautern67653 Germany Scientific Visualization Lab Technische Universität Kaiserslautern P. O. Box 3049 Kaiserslautern67653 Germany

We present PREVIS, a visual analytics tool, enhancing machine learning performance analysis in engineering applications. The presented toolchain allows for a direct comparison of regression models. In addition, we provide a methodology to visualize the impact of regression errors on the underlying field of interest in the original domain, the part geometry, via exploiting standard interpolation methods. Further, we allow a real-time preview of user-driven parameter changes in the displacement field via visual interpolation. This allows for fast and accountable online change management. We demonstrate the effectiveness with an ex-ante optimization of an automotive engine hood. © 2022 Elsevier B.V.. All rights reserved.

关键词： Quality control

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Interactive quality inspection of measured deviations in sheet metal assemblies 2

Interactive quality inspection of measured deviations in she...

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2nd International Conference of the DFG International Research Training Group 2057 - Physical Modeling for Virtual Manufacturing, iPMVM 2020

作者： Claus, Felix Hagen, Hans Leonhardt, Viktor Leitte, Heike Hamann, Bernd Computer Graphics and HCI Lab Computer Science Department Technische Universität Kaiserslautern Germany Scientific Visualization Lab Computer Science Department Technische Universität Kaiserslautern Germany Visual Information Analysis Computer Science Department Technische Universität Kaiserslautern Germany Department of Computer Science University of California DavisCA95616 United States

ISBN: (纸本)9783959771832

We present an exploratory data analysis approach for finite element (FE) simulations to interactively inspect measured deviations in sheet metals arising in automotive applications. Exterior car body parts consist of large visible surfaces, and strict tolerances must be met by them to satisfy both aesthetic requirements and quality performance requirements. To fulfill quality requirements like gap and flushness, exterior vehicle components have adjustable mechanical boundaries. These boundaries are used to influence the shape and position of a sheet metal part relative to its chassis. We introduce a method that supports an inspection engineer with an interactive framework that makes possible a detailed analysis of measured sheet metal deviation fields generated from 3D scans. An engineer can interactively change boundary conditions and obtains the resulting deviation field in real-time. Thus, it is possible to determine viable and desirable adjustments efficiently, leading to time and cost savings in the assembly process. © Felix Claus, Hans Hagen, Viktor Leonhardt, Heike Leitte, and Bernd Hamann.

关键词： Inspection

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