Browsing by Author "Knauthe, Volker"

Now showing 1 - 6 of 6
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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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    Data Reconstruction from Colored Slice-and-Dice Treemaps
    (The Eurographics Association, 2020) Henkel, Markus; Knauthe, Volker; Landesberger, Tatiana von; Guthe, Stefan; Krüger, Jens and Niessner, Matthias and Stückler, Jörg
    Treemaps illustrate hierarchical data, such as file systems or budget structures. Colors are often used to encode additional information or to emphasize the tree structure. Given a treemap, one may want to retrieve the underlying data. However, treemap reconstruction is challenging, as the inner tree structure needs to be derived almost exclusively from leaf node rectangles. Furthermore, treemaps are well known to suffer from ambiguities, i.e., different input data may produce the same drawing. We present a novel reconstruction approach for slice-and-dice treemaps. Moreover, we evaluate the influence of five color schemes to resolve ambiguities. Our work can be used for the reproducibility of published data and for assessing ambiguities in slice-and-dice treemaps.
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    Fitness of General-Purpose Monocular Depth Estimation Architectures for Transparent Structures
    (The Eurographics Association, 2022) Wirth, Tristan; Jamili, Aria; Buelow, Max von; Knauthe, Volker; Guthe, Stefan; Pelechano, Nuria; Vanderhaeghe, David
    Due to material properties, monocular depth estimation of transparent structures is inherently challenging. Recent advances leverage additional knowledge that is not available in all contexts, i.e., known shape or depth information from a sensor. General-purpose machine learning models, that do not utilize such additional knowledge, have not yet been explicitly evaluated regarding their performance on transparent structures. In this work, we show that these models show poor performance on the depth estimation of transparent structures. However, fine-tuning on suitable data sets, such as ClearGrasp, increases their estimation performance on the task at hand. Our evaluations show that high performance on general-purpose benchmarks translates well into performance on transparent objects after fine-tuning. Furthermore, our analysis suggests, that state-of-theart high-performing models are not able to capture a high grade of detail from both the image foreground and background at the same time. This finding shows the demand for a combination of existing models to further enhance depth estimation quality.
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    A Post Processing Technique to Automatically Remove Floater Artifacts in Neural Radiance Fields
    (The Eurographics Association and John Wiley & Sons Ltd., 2023) Wirth, Tristan; Rak, Arne; Knauthe, Volker; Fellner, Dieter W.; Chaine, Raphaëlle; Deng, Zhigang; Kim, Min H.
    Neural Radiance Fields have revolutionized Novel View Synthesis by providing impressive levels of realism. However, in most in-the-wild scenes they suffer from floater artifacts that occur due to sparse input images or strong view-dependent effects. We propose an approach that uses neighborhood based clustering and a consistency metric on NeRF models trained on different scene scales to identify regions that contain floater artifacts based on Instant-NGPs multiscale occupancy grids. These occupancy grids contain the position of relevant optical densities in the scene. By pruning the regions that we identified as containing floater artifacts, they are omitted during the rendering process, leading to higher quality resulting images. Our approach has no negative runtime implications for the rendering process and does not require retraining of the underlying Multi Layer Perceptron. We show on a qualitative base, that our approach is suited to remove floater artifacts while preserving most of the scenes relevant geometry. Furthermore, we conduct a comparison to state-of-the-art techniques on the Nerfbusters dataset, that was created with measuring the implications of floater artifacts in mind. This comparison shows, that our method outperforms currently available techniques. Our approach does not require additional user input, but can be be used in an interactive manner. In general, the presented approach is applicable to every architecture that uses an explicit representation of a scene's occupancy distribution to accelerate the rendering process.
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    Reconstructing Bounding Volume Hierarchies from Memory Traces of Ray Tracers
    (The Eurographics Association, 2022) Buelow, Max von; Stensbeck, Tobias; Knauthe, Volker; Guthe, Stefan; Fellner, Dieter W.; Yang, Yin; Parakkat, Amal D.; Deng, Bailin; Noh, Seung-Tak
    The ongoing race to improve computer graphics leads to more complex GPU hardware and ray tracing techniques whose internal functionality is sometimes hidden to the user. Bounding volume hierarchies and their construction are an important performance aspect of such ray tracing implementations. We propose a novel approach that utilizes binary instrumentation to collect memory traces and then uses them to extract the bounding volume hierarchy (BVH) by analyzing access patters. Our reconstruction allows combining memory traces captured from multiple ray tracing views independently, increasing the reconstruction result. It reaches accuracies of 30% to 45% when comparing against the ground-truth BVH used for ray tracing a single view on a simple scene with one object. With multiple views it is even possible to reconstruct the whole BVH, while we already achieve 98% with just seven views. Because our approach is largely independent of the data structures used internally, these accurate reconstructions serve as a first step into estimation of unknown construction techniques of ray tracing implementations.
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    Segmentation-Based Near-Lossless Compression of Multi-View Cultural Heritage Image Data
    (The Eurographics Association, 2020) Buelow, Max von; Tausch, Reimar; Knauthe, Volker; Wirth, Tristan; Guthe, Stefan; Santos, Pedro; Fellner, Dieter W.; Spagnuolo, Michela and Melero, Francisco Javier
    Cultural heritage preservation using photometric approaches received increasing significance in the past years. Capturing of these datasets is usually done with high-end cameras at maximum image resolution enabling high quality reconstruction results while leading to immense storage consumptions. In order to maintain archives of these datasets, compression is mandatory for storing them at reasonable cost. In this paper, we make use of the mostly static background of the capturing environment that does not directly contribute information to 3d reconstruction algorithms and therefore may be approximated using lossy techniques. We use a superpixel and figure-ground segmentation based near-lossless image compression algorithm that transparently decides if regions are relevant for later photometric reconstructions. This makes sure that the actual artifact or structured background parts are compressed with lossless techniques. Our algorithm achieves compression rates compared to the PNG image compression standard ranging from 1:2 to 1:4 depending on the artifact size.