Browsing by Author "Kuijper, Arjan"

Now showing 1 - 5 of 5
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    Alignment and Reassembly of Broken Specimens for Creep Ductility Measurements
    (The Eurographics Association, 2022) Knauthe, Volker; Kraus, Maurice; Buelow, Max von; Wirth, Tristan; Rak, Arne; Merth, Laurenz; Erbe, Alexander; Kontermann, Christian; Guthe, Stefan; Kuijper, Arjan; Fellner, Dieter W.; Bender, Jan; Botsch, Mario; Keim, Daniel A.
    Designing new types of heat-resistant steel components is an important and active research field in material science. It requires detailed knowledge of the inherent steel properties, especially concerning their creep ductility. Highly precise automatic stateof- the-art approaches for such measurements are very expensive and often times invasive. The alternative requires manual work from specialists and is time consuming and unrobust. In this paper, we present a novel approach that uses a photometric scanning system for capturing the geometry of steel specimens, making further measurement extractions possible. In our proposed system, we apply calibration for pan angles that occur during capturing and a robust reassembly for matching two broken specimen pieces to extract the specimen's geometry. We compare our results against µCT scans and found that it deviates by 0.057mm on average distributed over the whole specimen for a small amount of 36 captured images. Additionally, comparisons to manually measured values indicate that our system leads to more robust measurements.
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    Efficient Global Registration for Nominal/Actual Comparisons
    (The Eurographics Association, 2018) Berkei, Sarah; Limper, Max; Hörr, Christian; Kuijper, Arjan; Beck, Fabian and Dachsbacher, Carsten and Sadlo, Filip
    We investigate global registration methods for Nominal/Actual comparisons, using precise, high-resolution 3D scans. First we summarize existing approaches and requirements for this field of application. We then demonstrate that a basic RANSAC strategy, along with a slightly modified version of basic building blocks, can lead to a high global registration performance at moderate registration times. Specifically, we introduce a simple feedback loop that exploits the fast convergence of the ICP algorithm to efficiently speed up the search for a valid global alignment. Using the example of 3D printed parts and range images acquired by two different high-precision 3D scanners for quality control, we show that our method can be efficiently used for Nominal/Actual comparison. For this scenario, the proposed algorithm significantly outperforms the current state of the art, with regards to registration time and success rate.
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    A GPU Ray Tracing Implementation for Triangular Grid Primitives
    (The Eurographics Association, 2023) Buelow, Max von; Kuijper, Arjan; Fellner, Dieter W.; Abey Campbell; Claudia Krogmeier; Gareth Young
    Triangular grid primitives are a new technique for more efficient handling of memory intensive meshes, also called micro meshes in recent proprietary hardware implementations. This makes it a technique with high potential in the area of virtual environments where hardware capabilities are typically limited. In this poster, we focus on software ray tracing on GPUs and present a novel, easy-to-implement approach that uses a two-level bounding volume hierarchy (BVH) to accelerate these grids. The primary goal of our work is to make the technology more accessible by focusing on standard GPU devices without hardware ray tracing units. With our approach, we are able to encode geometry and BVH with approximately 7.5 bytes per triangle, reducing standard representations by a factor of 3.73 while reducing BVH construction time. Our data structure achieves a peak performance impact of 16% for a three-level subdivision.
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    Interactive Visualization of Machine Learning Model Results Predicting Infection Risk
    (The Eurographics Association, 2022) Schäfer, Steffen; Baumgartl, Tom; Wulff, Antje; Kuijper, Arjan; Marschollek, Michael; Scheithauer, Simone; von Landesberger, Tatiana; Krone, Michael; Lenti, Simone; Schmidt, Johanna
    We present a novel visual-interactive interface to show results of a machine learning algorithm, which predicts the infection probability for patients in hospitals. The model result data is complex and needs to be presented in a clear and intuitive way to microbiology and infection control experts in hospitals. Our visual-interactive interface offers linked views which allow for detailed analysis of the model results. Feedback from microbiology and infection control experts showed that they were able to extract new insights regarding outbreaks and transmission pathways.
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    One-to-many Reconstruction of 3D Geometry of cultural Artifacts using a synthetically trained Generative Model
    (The Eurographics Association, 2023) Pöllabauer, Thomas; Kühn, Julius; Li, Jiayi; Kuijper, Arjan; Bucciero, Alberto; Fanini, Bruno; Graf, Holger; Pescarin, Sofia; Rizvic, Selma
    Estimating the 3D shape of an object using a single image is a difficult problem. Modern approaches achieve good results for general objects, based on real photographs, but worse results on less expressive representations such as historic sketches. Our automated approach generates a variety of detailed 3D representation from a single sketch, depicting a medieval statue, and can be guided by multi-modal inputs, such as text prompts. It relies solely on synthetic data for training, making it adoptable even in cases of only small numbers of training examples. Our solution allows domain experts such as a curators to interactively reconstruct potential appearances of lost artifacts.