VMV: Vision, Modeling, and Visualization

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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.
Astray: A Performance-Portable Geodesic Ray Tracer
(The Eurographics Association, 2022) Demiralp, Ali Can; Krüger, Marcel; Chao, Chu; Kuhlen, Torsten W.; Gerrits, Tim; Bender, Jan; Botsch, Mario; Keim, Daniel A.
Geodesic ray tracing is the numerical method to compute the motion of matter and radiation in spacetime. It enables visualization of the geometry of spacetime and is an important tool to study the gravitational fields in the presence of astrophysical phenomena such as black holes. Although the method is largely established, solving the geodesic equation remains a computationally demanding task. In this work, we present Astray; a high-performance geodesic ray tracing library capable of running on a single or a cluster of computers equipped with compute or graphics processing units. The library is able to visualize any spacetime given its metric tensor and contains optimized implementations of a wide range of spacetimes, including commonly studied ones such as Schwarzschild and Kerr. The performance of the library is evaluated on standard consumer hardware as well as a compute cluster through strong and weak scaling benchmarks. The results indicate that the system is capable of reaching interactive frame rates with increasing use of high-performance computing resources. We further introduce a user interface capable of remote rendering on a cluster for interactive visualization of spacetimes.
Automatic Generation of Saliency-based Areas of Interest for the Visualization and Analysis of Eye-tracking Data
(The Eurographics Association, 2018) Fuhl, Wolfgang; Kuebler, Thomas; Santini, Thiago; Kasneci, Enkelejda; Beck, Fabian and Dachsbacher, Carsten and Sadlo, Filip
Areas of interest (AOIs) are a powerful basis for the analysis and visualization of eye-tracking data. They allow to relate eyetracking metrics to semantic stimulus regions and to perform further statistics. In this work, we propose a novel method for the automated generation of AOIs based on saliency maps. In contrast to existing methods from the state-of-the-art, which generate AOIs based on eye-tracking data, our method generates AOIs based solely on the stimulus saliency, mimicking thus our natural vision. This way, our method is not only independent of the eye-tracking data, but allows to work AOI-based even for complex stimuli, such as abstract art, where proper manual definition of AOIs is not trivial. For evaluation, we cross-validate support vector machine classifiers with the task of separating visual scanpaths of art experts from those of novices. The motivation for this evaluation is to use AOIs as projection functions and to evaluate their robustness on different feature spaces. A good AOI separation should result in different feature sets that enable a fast evaluation with a widely automated work-flow. The proposed method together with the data shown in this paper is available as part of the software EyeTrace [?] http://www.ti.unituebingen. de/Eyetrace.1751.0.html.
CoSi: Visual Comparison of Similarities in High-Dimensional Data Ensembles
(The Eurographics Association, 2021) Heim, Anja; Gröller, Eduard; Heinzl, Christoph; Andres, Bjoern and Campen, Marcel and Sedlmair, Michael
Comparative analysis of multivariate datasets, e.g. of advanced materials regarding the characteristics of internal structures (fibers, pores, etc.), is of crucial importance in various scientific disciplines. Currently domain experts in materials science mostly rely on sequential comparison of data using juxtaposition. Our work assists domain experts to perform detailed comparative analyses of large ensemble data in materials science applications. For this purpose, we developed a comparative visualization framework, that includes a tabular overview and three detailed visualization techniques to provide a holistic view on the similarities in the ensemble. We demonstrate the applicability of our framework on two specific usage scenarios and verify its techniques using a qualitative user study with 12 material experts. The insights gained from our work represent a significant advancement in the field of comparative material analysis of high-dimensional data. Our framework provides experts with a novel perspective on the data and eliminates the need for time-consuming sequential exploration of numerical data.
Evaluation of Volume Representation Networks for Meteorological Ensemble Compression
(The Eurographics Association, 2022) Höhlein, Kevin; Weiss, Sebastian; Necker, Tobias; Weissmann, Martin; Miyoshi, Takemasa; Westermann, Rüdiger; Bender, Jan; Botsch, Mario; Keim, Daniel A.
Recent studies have shown that volume scene representation networks constitute powerful means to transform 3D scalar fields into extremely compact representations, from which the initial field samples can be randomly accessed. In this work, we evaluate the capabilities of such networks to compress meteorological ensemble data, which are comprised of many separate weather forecast simulations. We analyze whether these networks can effectively exploit similarities between the ensemble members, and how alternative classical compression approaches perform in comparison. Since meteorological ensembles contain different physical parameters with various statistical characteristics and variations on multiple scales of magnitude, we analyze the impact of data normalization schemes on learning quality. Along with an evaluation of the trade-offs between reconstruction quality and network model parameterization, we compare compression ratios and reconstruction quality for different model architectures and alternative compression schemes.
Painterly Rendering using Limited Paint Color Palettes
(The Eurographics Association, 2018) Lindemeier, Thomas; Gülzow, J. Marvin; Deussen, Oliver; Beck, Fabian and Dachsbacher, Carsten and Sadlo, Filip
We present a painterly rendering method for digital painting systems as well as visual feedback based painting machines that automatically extracts color palettes from images and computes mixture recipes for these from a set of real base paint colors based on the Kubelka-Munk theory. In addition, we present a new algorithm for distributing stroke candidates, which creates paintings with sharp details and contrasts. Our system is able to predict dry compositing of thinned or thick paint colors using an evaluation scheme based on example data collected from a calibration step and optical blending. We show results generated using a software stroke-based renderer and a painting machine.
Visualizing Temporal-Thematic Patterns in Text Collections
(The Eurographics Association, 2021) Knabben, Moritz; Baumann, Martin; Blascheck, Tanja; Ertl, Thomas; Koch, Steffen; Andres, Bjoern and Campen, Marcel and Sedlmair, Michael
Visualizing the temporal evolution of texts is relevant for many domains that seek to gain insight from text repositories. However, existing visualization methods for text collections do not show fine-grained temporal-thematic patterns. Therefore, we developed and analyzed a new visualization method that aims at uncovering such patterns. Specifically, we project texts to one dimension, which allows positioning texts in a 2D diagram of projection space and time. For projection, we employed two manifold learning algorithms: the self-organizing map (SOM) and UMAP. To assess the utility of our method, we experimented with real-world datasets and discuss the resulting visualizations. We find our method facilitates relating patterns and extracting associated texts beyond what is possible with previous techniques. We also conducted interviews with historians to show that our prototypical system supports domain experts in their analysis tasks.
WithTeeth: Denture Preview in Augmented Reality
(The Eurographics Association, 2018) Amirkhanov, Aleksandr; Amirkhanov, Artem; Bernhard, Matthias; Toth, Zsolt; Stiller, Sabine; Geier, Andreas; Gröller, Eduard; Mistelbauer, Gabriel; Beck, Fabian and Dachsbacher, Carsten and Sadlo, Filip
Dentures are prosthetic devices replacing missing or damaged teeth, often used for dental reconstruction. Dental reconstruction improves the functional state and aesthetic appearance of teeth. State-of-the-art methods used by dental technicians typically do not include the aesthetic analysis, which often leads to unsatisfactory results for patients. In this paper, we present a virtual mirror approach for a dental treatment preview in augmented reality. Different denture presets are visually evaluated and compared by switching them on the fly. Our main goals are to provide a virtual dental treatment preview to facilitate early feedback, and hence to build the confidence and trust of patients in the outcome. The workflow of our algorithm is as follows. First, the face is detected and 2D facial landmarks are extracted. Then, 3D pose estimation of upper and lower jaws is performed and high-quality 3D models of the upper and lower dentures are fitted. The fitting uses the occlusal plane angle as determined mnually by dental technicians. To provide a realistic impression of the virtual teeth, the dentures are rendered with motion blur. We demonstrate the robustness and visual quality of our approach by comparing the results of a webcam to a DSLR camera under natural, as well as controlled lighting conditions.

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