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 imag...
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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, e...
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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.
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, tre...
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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...
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.
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 imme...
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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.
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 sever...
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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 w...
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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 pro...
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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 ...
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