Browsing by Author "Klein, Reinhard"

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    Fabric Appearance Benchmark
    (The Eurographics Association, 2020) Merzbach, Sebastian; Klein, Reinhard; Ritschel, Tobias and Eilertsen, Gabriel
    Appearance modeling is a difficult problem that still receives considerable attention from the graphics and vision communities. Though recent years have brought a growing number of high-quality material databases that have sparked new research, there is a general lack of evaluation benchmarks for performance assessment and fair comparisons between competing works. We therefore release a new dataset and pose a public challenge that will enable standardized evaluations. For this we measured 56 fabric samples with a commercial appearance scanner. We publish the resulting calibrated HDR images, along with baseline SVBRDF fits. The challenge is to recreate, under known light and view sampling, the appearance of a subset of unseen images. User submissions will be automatically evaluated and ranked by a set of standard image metrics.
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    Interactive Formation of Statistical Hypotheses in Diffusion Tensor Imaging
    (The Eurographics Association, 2019) Abbasloo, Amin; Wiens, Vitalis; Schmidt-Wilcke, Tobias; Sundgren, Pia; Klein, Reinhard; Schultz, Thomas; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    When Diffusion Tensor Imaging (DTI) is used in clinical studies, statistical hypothesis testing is the standard approach to establish significant differences between groups, such as patients and healthy controls. However, diffusion tensors contain six degrees of freedom, and the most commonly used univariate tests reduce them to a single scalar, such as Fractional Anisotropy. Multivariate tests that account for the full tensor information have been developed, but have not been widely adopted in practice. Based on analyzing the limitations of existing univariate and multivariate tests, we argue that it is beneficial to use a more flexible, steerable test. Therefore, we introduce a test that can be customized to include any subset of tensor attributes that are relevant to the analysis task at hand. We also present a visual analytics system that supports the exploratory task of customizing it to a specific scenario. Our system closely integrates quantitative analysis with suitable visualizations. It links spatial and abstract views to reveal clusters of strong differences, to relate them to the affected anatomical structures, and to visually compare the results of different tests. A use case is presented in which our system leads to the formation of several new hypotheses about the effects of systemic lupus erythematosus on water diffusion in the brain.