Browsing by Author "Frey, Steffen"

Now showing 1 - 6 of 6
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    Optimizing Grid Layouts for Level-of-Detail Exploration of Large Data Collections
    (The Eurographics Association and John Wiley & Sons Ltd., 2022) Frey, Steffen; Borgo, Rita; Marai, G. Elisabeta; Schreck, Tobias
    This paper introduces an optimization approach for generating grid layouts from large data collections such that they are amenable to level-of-detail presentation and exploration. Classic (flat) grid layouts visually do not scale to large collections, yielding overwhelming numbers of tiny member representations. The proposed local search-based progressive optimization scheme generates hierarchical grids: leaves correspond to one grid cell and represent one member, while inner nodes cover a quadratic range of cells and convey an aggregate of contained members. The scheme is solely based on pairwise distances and jointly optimizes for homogeneity within inner nodes and across grid neighbors. The generated grids allow to present and flexibly explore the whole data collection with arbitrary local granularity. Diverse use cases featuring large data collections exemplify the application: stock market predictions from a Black-Scholes model, channel structures in soil from Markov chain Monte Carlo, and image collections with feature vectors from neural network classification models. The paper presents feedback by a domain scientist, compares against previous approaches, and demonstrates visual and computational scalability to a million members, surpassing classic grid layout techniques by orders of magnitude.
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    Parallel Compositing of Volumetric Depth Images for Interactive Visualization of Distributed Volumes at High Frame Rates
    (The Eurographics Association, 2023) Gupta, Aryaman; Incardona, Pietro; Brock, Anton; Reina, Guido; Frey, Steffen; Gumhold, Stefan; Günther, Ulrik; Sbalzarini, Ivo F.; Bujack, Roxana; Pugmire, David; Reina, Guido
    We present a parallel compositing algorithm for Volumetric Depth Images (VDIs) of large three-dimensional volume data. Large distributed volume data are routinely produced in both numerical simulations and experiments, yet it remains challenging to visualize them at smooth, interactive frame rates. VDIs are view-dependent piecewise constant representations of volume data that offer a potential solution. They are more compact and less expensive to render than the original data. So far, however, there is no method for generating VDIs from distributed data. We propose an algorithm that enables this by sort-last parallel generation and compositing of VDIs with automatically chosen content-adaptive parameters. The resulting composited VDI can then be streamed for remote display, providing responsive visualization of large, distributed volume data.
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    PGV 2019: Frontmatter
    (The Eurographics Association, 2019) Childs, Hank; Frey, Steffen; Childs, Hank and Frey, Steffen
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    PGV 2020: Frontmatter
    (The Eurographics Association, 2020) Frey, Steffen; Huang, Jian; Sadlo, Filip; Frey, Steffen and Huang, Jian and Sadlo, Filip
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    Visual Analysis of Popping in Progressive Visualization
    (The Eurographics Association, 2021) Waterink, Ethan; Kosinka, Jiri; Frey, Steffen; Frosini, Patrizio and Giorgi, Daniela and Melzi, Simone and Rodolà, Emanuele
    Progressive visualization allows users to examine intermediate results while they are further refined in the background. This makes them increasingly popular when dealing with large data and computationally expensive tasks. The characteristics of how preliminary visualizations evolve over time are crucial for efficient analysis; in particular unexpected disruptive changes between iterations can significantly hamper the user experience. This paper proposes a visualization framework to analyze the refinement behavior of progressive visualization. We particularly focus on sudden significant changes between the iterations, which we denote as popping artifacts, in reference to undesirable visual effects in the context of level of detail representations in computer graphics. Our visualization approach conveys where in image space and when during the refinement popping artifacts occur. It allows to compare across different runs of stochastic processes, and supports parameter studies for gaining further insights and tuning the algorithms under consideration. We demonstrate the application of our framework and its effectiveness via two diverse use cases with underlying stochastic processes: adaptive image space sampling, and the generation of grid layouts.
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    Visual Analysis of Two‐Phase Flow Displacement Processes in Porous Media
    (© 2022 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2022) Frey, Steffen; Scheller, Stefan; Karadimitriou, Nikolaos; Lee, Dongwon; Reina, Guido; Steeb, Holger; Ertl, Thomas; Hauser, Helwig and Alliez, Pierre
    We developed a new visualization approach to gain a better understanding of the displacement of one fluid phase by another in porous media. This is based on a recent experimental parameter study with varying capillary numbers and viscosity ratios. We analyse the temporal evolution of characteristic values in this two‐phase flow scenario and discuss how to directly compare experiments across different temporal scales. To enable spatio‐temporal analysis, we introduce a new abstract visual representation showing which paths through the porous medium were occupied and for how long. These transport networks allow to assess the impact of different acting forces and they are designed to yield expressive comparability and linking to the experimental parameter space both supported by additional visual cues. This joint work of porous media experts and visualization researchers yields new insights regarding two‐phase flow on the microscale, and our visualization approach contributes towards the overarching goal of the domain scientists to characterize porous media flow based on capillary numbers and viscosity ratios.