Browsing by Author "Hauser, Helwig"

Now showing 1 - 8 of 8
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    2019_editorial_v2
    (© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Hauser, Helwig; Benes, Bedrich; Benes, Bedrich and Hauser, Helwig
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    Dual Radial Set
    (The Eurographics Association, 2020) Matkovic, Kresimir; Gracanin, Denis; Bardun, Matea; Splechtna, Rainer; Hauser, Helwig; Turkay, Cagatay and Vrotsou, Katerina
    Set-typed data visualizations require novel interactive representations, especially when visualizing multiple set-typed data attributes. The challenge is how to effectively analyze relations between data elements from different set-typed attributes. We build on Radial Set view to support simultaneous visualization of two set-typed attributes. The main contributions include: Dual Radial Set view that supports simultaneous visualization of two groups of sets; an extension of Radial Set view that can display empty sets; and two new view configurations, the equal sector size and the relative-size scaled sectors. The two new view configurations also can be applied to the original Radial Set view. We conducted an informal evaluation using a movies data set as a case study. The evaluation results demonstrate the advantages of the proposed approach.
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    Editorial
    (© 2021 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2021) Hauser, Helwig; Benes, Bedrich; Benes, Bedrich and Hauser, Helwig
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    Editorial
    (Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2023) Alliez, Pierre; Hauser, Helwig; Hauser, Helwig and Alliez, Pierre
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    Focus+Context Exploration of Hierarchical Embeddings
    (The Eurographics Association and John Wiley & Sons Ltd., 2019) Höllt, Thomas; Vilanova, Anna; Pezzotti, Nicola; Lelieveldt, Boudewijn P. F.; Hauser, Helwig; Gleicher, Michael and Viola, Ivan and Leitte, Heike
    Hierarchical embeddings, such as HSNE, address critical visual and computational scalability issues of traditional techniques for dimensionality reduction. The improved scalability comes at the cost of the need for increased user interaction for exploration. In this paper, we provide a solution for the interactive visual Focus+Context exploration of such embeddings. We explain how to integrate embedding parts from different levels of detail, corresponding to focus and context groups, in a joint visualization. We devise an according interaction model that relates typical semantic operations on a Focus+Context visualization with the according changes in the level-of-detail-hierarchy of the embedding, including also a mode for comparative Focus+Context exploration and extend HSNE to incorporate the presented interaction model. In order to demonstrate the effectiveness of our approach, we present a use case based on the visual exploration of multi-dimensional images.
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    On KDE-based Brushing in Scatterplots and how it Compares to CNN-based Brushing
    (The Eurographics Association, 2019) Fan, Chaoran; Hauser, Helwig; Archambault, Daniel and Nabney, Ian and Peltonen, Jaakko
    In this paper, we investigate to which degree the human should be involved into the model design and how good the empirical model can be with more careful design. To find out, we extended our previously published Mahalanobis brush (the best current empirical model in terms of accuracy for brushing points in a scatterplot) by further incorporating the data distribution information that is captured by the kernel density estimation (KDE). Based on this work, we then include a short discussion between the empirical model, designed in detail by an expert and the deep learning-based model that is learned from user data directly.
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    Revealing Multimodality in Ensemble Weather Prediction
    (The Eurographics Association, 2021) Galmiche, Natacha; Hauser, Helwig; Spengler, Thomas; Spensberger, Clemens; Brun, Morten; Blaser, Nello; Archambault, Daniel and Nabney, Ian and Peltonen, Jaakko
    Ensemble methods are widely used to simulate complex non-linear systems and to estimate forecast uncertainty. However, visualizing and analyzing ensemble data is challenging, in particular when multimodality arises, i.e., distinct likely outcomes. We propose a graph-based approach that explores multimodality in univariate ensemble data from weather prediction. Our solution utilizes clustering and a novel concept of life span associated with each cluster. We applied our method to historical predictions of extreme weather events and illustrate that our method aids the understanding of the respective ensemble forecasts.
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    Trends & Opportunities in Visualization for Physiology: A Multiscale Overview
    (The Eurographics Association and John Wiley & Sons Ltd., 2022) Garrison, Laura A.; Kolesar, Ivan; Viola, Ivan; Hauser, Helwig; Bruckner, Stefan; Bruckner, Stefan; Turkay, Cagatay; Vrotsou, Katerina
    Combining elements of biology, chemistry, physics, and medicine, the science of human physiology is complex and multifaceted. In this report, we offer a broad and multiscale perspective on key developments and challenges in visualization for physiology. Our literature search process combined standard methods with a state-of-the-art visual analysis search tool to identify surveys and representative individual approaches for physiology. Our resulting taxonomy sorts literature on two levels. The first level categorizes literature according to organizational complexity and ranges from molecule to organ. A second level identifies any of three high-level visualization tasks within a given work: exploration, analysis, and communication. The findings of this report may be used by visualization researchers to understand the overarching trends, challenges, and opportunities in visualization for physiology and to provide a foundation for discussion and future research directions in this area.