Browsing by Author "Fellner, Dieter W."

Now showing 1 - 7 of 7
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    AI Based Image Segmentation of Cultural Heritage Objects used for Multi-View Stereo 3D Reconstructions
    (The Eurographics Association, 2023) Kutlu, Hasan; Brucker, Felix; Kallendrusch, Ben; Santos, Pedro; Fellner, Dieter W.; Bucciero, Alberto; Fanini, Bruno; Graf, Holger; Pescarin, Sofia; Rizvic, Selma
    Image segmentation (or masking) finds a very useful use case within 3D reconstruction of cultural heritage objects. The 3D reconstructions can be accelerated, reconstructing the object without any background noise. Conventional segmentation methods can calculate erroneous masks for certain objects and environments, which can lead to errors within the reconstruction: Parts of the 3D reconstruction may be missing or are incorrectly reconstructed, which contradicts adequate archiving. The automated iterative Multi-View Stereo (MVS) scanning process makes it necessary to obtain masks that reconstruct the object in the best possible way, regardless of the environment, the stabilizing mount, the color of the background and the object. In addition, it should not be necessary to tweak the best possible parameters for conventional masking procedures and to create masks manually. State-of-the-art artificial intelligence (AI) segmentation networks will be trained and applied to the MVS scans to verify the behavior of the associated 3D reconstructions and the automated iterative scanning process. In addition, a comparison between different AI segmentation networks and a comparison between conventional masking methods and AI segmentation networks is performed.
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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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    CultArc3D_mini: Fully Automatic Zero-Button 3D Replicator
    (The Eurographics Association, 2018) Ritz, Martin; Knuth, Martin; Santos, Pedro; Fellner, Dieter W.; Sablatnig, Robert and Wimmer, Michael
    3D scanning and 3D printing are two rapidly evolving domains, both generating results with a huge and growing spectrum of applications. Especially in Cultural Heritage, a massive and increasing amount of objects awaits digitization for various purposes, one of them being replication. Yet, current approaches to optical 3D digitization are semi-automatic at best and require great user effort whenever high quality is desired. With our solution we provide the missing link between both domains, and present a fully automatic 3D object replicator which does not require user interaction. The system consists of our photogrammetric 3D scanner CultArc3D_mini that captures an optimal image set for 3D geometry and texture reconstruction and even optical material properties of objects in only minutes, a conveyor system for automatic object feed-in and -out, a 3D printer, and our sensor-based process flow software that handles every single process step of the complex sequence from image acquisition, sensor-based object transportation, 3D reconstruction involving different kinds of calibrations, to 3D printing of the resulting virtual replica immediately after 3D reconstruction. Typically, one-button machines require the user to start the process by interacting over a user interface. Since positioning and pickup of objects is automatically registered, the only thing left for the user to do is placing an object at the entry and retrieving it from the exit after scanning. Shortly after, the 3D replica can be picked up from the 3D printer. Technically, we created a zero-button 3D replicator that provides high throughput digitization in 3D, requiring only minutes per object, and it is publicly showcased in action at 3IT Berlin.
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    Direct Limit Volumes: Constant-Time Limit Evaluation for Catmull-Clark Solids
    (The Eurographics Association, 2018) Altenhofen, Christian; Müller, Joel; Weber, Daniel; Stork, André; Fellner, Dieter W.; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    We present a novel approach for efficient limit volume evaluation on Catmull-Clark (CC) subdivision solids. Although several analogies exist between subdivision surfaces and subdivision volumes, extending Stam's limit evaluation technique from 2 to 3 dimensions is not straightforward, as irregularities and boundaries introduce new challenges in the volumetric case. We present new direct evaluation techniques for irregular volumetric topologies and boundary cells, which allow for calculating the limit of CC subdivision solids at arbitrary parameter values in constant time. Evaluation of limit points is a central aspect when using CC solids for applications such as simulation and multi-material additive manufacturing, or as a compact volumetric representation scheme for continuous scalar fields. We demonstrate that our approach is faster than existing evaluation techniques for every topological configuration or target parameter (u, v, w) that requires more than two local subdivision steps.
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    Fine-Grained Memory Profiling of GPGPU Kernels
    (The Eurographics Association and John Wiley & Sons Ltd., 2022) Buelow, Max von; Guthe, Stefan; Fellner, Dieter W.; Umetani, Nobuyuki; Wojtan, Chris; Vouga, Etienne
    Memory performance is a crucial bottleneck in many GPGPU applications, making optimizations for hardware and software mandatory. While hardware vendors already use highly efficient caching architectures, software engineers usually have to organize their data accordingly in order to efficiently make use of these, requiring deep knowledge of the actual hardware. In this paper we present a novel technique for fine-grained memory profiling that simulates the whole pipeline of memory flow and finally accumulates profiling values in a way that the user retains information about the potential region in the GPU program by showing these values separately for each allocation. Our memory simulator turns out to outperform state-of-theart memory models of NVIDIA architectures by a magnitude of 2.4 for the L1 cache and 1.3 for the L2 cache, in terms of accuracy. Additionally, we find our technique of fine grained memory profiling a useful tool for memory optimizations, which we successfully show in case of ray tracing and machine learning applications.
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    Fully Automatic Mechanical Scan Range Extension and Signal to Noise Optimization of a Lens-Shifted Structured Light System
    (The Eurographics Association, 2021) Kutlu, Hasan; Ritz, Martin; Santos, Pedro; Fellner, Dieter W.; Hulusic, Vedad and Chalmers, Alan
    Digitization of cultural heritage is of growing importance, both for its preservation for coming generations in the face of looming dangers of natural decay or intentional destruction, and current generations, that increasingly have access to virtual cultural heritage for interactive exploring or scientific analysis. These goals can only be achieved by 3D replicas at reasonable quality and resolution, to come as close as possible to the original. This brings about several challenges to overcome. The challenge of digitizing huge numbers of artefacts is addressed by CultLab3D, the first fully automatic 3D digitization system. Another challenge is the size of objects, as each digitization system is designed for a certain optimum measurement range, leaving which results in loss of quality. Due to optical and mechanical constraints, most systems are not able to faithfully reconstruct objects under a certain size limit in their full geometric detail. Historic coins are one good example, where the deterioration of the surface structure in most cases has progressed to a degree that it not even is perceptible through the fingernail. This challenge is addressed by a modular extension of CultLab3D, the MesoScanner, which is a structured light system that breaks limits in depth resolution through a mechanical lens-shifting extension, allowing physically shifting of fringe patterns on top of the well-known multi-period phase shift method. This is where this work adds two major improvements: First, the signal to noise ratio and thus reconstruction quality has been improved significantly through several algorithmic processing steps. Second, the physical limitation of the measurement range was removed using a 2D actuator steering the object mount, thus allowing for a measurement range at theoretically arbitrary size. This opens up the fully automatic handling of two scenarios: Complete digitization of objects exceeding the measurement range, and unsupervised digitization of large collections of small objects in one run.
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    Massively Parallel Adaptive Collapsing of Edges for Unstructured Tetrahedral Meshes
    (The Eurographics Association, 2023) Ströter, Daniel; Stork, André; Fellner, Dieter W.; Bikker, Jacco; Gribble, Christiaan
    Many tasks in computer graphics and engineering involve unstructured tetrahedral meshes. Numerical methods such as the finite element method (FEM) oftentimes use tetrahedral meshes to compute a solution for complex problems such as physicallybased simulation or shape deformation. As each tetrahedron costs computationally, coarsening tetrahedral meshes typically reduces the overhead of numerical methods, which is attractive for interactive applications. In order to enable reduction of the tetrahedron count, we present a quick adaptive coarsening method for unstructured tetrahedral meshes. Our method collapses edges using the massively parallel processing power of present day graphics processing units (GPU)s to achieve run times of up to one order of magnitude faster than sequential collapsing. For efficient exploitation of parallel processing power, we contribute a quick method for finding a compact set of conflict-free sub-meshes, which results in up to 59% fewer parallel collapsing iterations compared to the state of the art massively parallel conflict detection.