VMV2020

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https://diglib.eg.org/handle/10.2312/2632934

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Browsing VMV2020 by Subject "Computing methodologies"

Now showing 1 - 6 of 6
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    A Compact Patch-Based Representation for Technical Mesh Models
    (The Eurographics Association, 2020) Kammann, Lars; Menzel, Stefan; Botsch, Mario; Krüger, Jens and Niessner, Matthias and Stückler, Jörg
    We present a compact and intuitive geometry representation for technical models initially given as triangle meshes. For CADlike models the defining features often coincide with the intersection between smooth surface patches. Our algorithm therefore first segments the input model into patches of constant curvature. The intersections between these patches are encoded through Bézier curves of adaptive degree, the patches enclosed by them are encoded by their (constant) mean and Gaussian curvatures. This sparse geometry representation enables intuitive understanding and editing by manipulating either the patches' curvature values and/or the feature curves. During decoding/reconstruction we exploit remeshing and hence are independent of the underlying triangulation, such that besides the feature curve topology no additional connectivity information has to be stored. We also enforce discrete developability for patches with vanishing Gaussian curvature in order to obtain straight ruling lines.
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    Multi-Layer Alpha Tracing
    (The Eurographics Association, 2020) Brüll, Felix; Grosch, Thorsten; Krüger, Jens and Niessner, Matthias and Stückler, Jörg
    Rendering many transparent surfaces in real-time is still an open problem. We introduce two techniques for fast transparency rendering with ray tracing hardware, one being exact and the other being approximate but of high quality. Our approximate technique is called Multi-Layer Alpha Tracing, operates in bounded memory and is up to 60% faster than naive ray traversal. It outperforms existing rasterization techniques in terms of image quality and performance while maintaining a small memory footprint. It can also be used to accelerate ray tracing of transparent objects for the reflected rays.
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    Portal-Based Path Perturbation for Metropolis Light Transport
    (The Eurographics Association, 2020) Otsu, Hisanari; Hanika, Johannes; Dachsbacher, Carsten; Krüger, Jens and Niessner, Matthias and Stückler, Jörg
    Light transport simulation in scenes with difficult visibility still remains a challenging problem. Markov chain Monte Carlo (MCMC) rendering is often employed for such configurations. It generates a sequence of correlated light transport paths by iteratively mutating the current state, a path, to another. Since the proposed path is correlated to the current path, MCMC can explore regions of the path space, also with difficult visibility, once they have been found. To improve the efficiency of the exploration, we propose a path mutation strategy making use of the concept of portals. Portals are user-defined objects in the scene to guide the sampling of the difficult visibility, which have been employed in the context of non-MCMC rendering. Our mutation strategy perturbs a path edge around the intersection point of the edge and the portal, instead of perturbing the edge by moving a path vertex as in the ordinary path mutation strategies. This reduces the probability for the proposed path being rejected due to changes in visibility.
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    Real-time High-resolution Visualisation
    (The Eurographics Association, 2020) Frieß, Florian; Müller, Christoph; Ertl, Thomas; Krüger, Jens and Niessner, Matthias and Stückler, Jörg
    While visualisation often strives for abstraction, the interactive exploration of large scientific data sets like densely sampled 3D fields or massive particle data sets still benefits from rendering their graphical representation in large detail on high-resolution displays such as Powerwalls or tiled display walls driven by multiple GPUs or even GPU clusters. Such visualisation systems are typically rather unique in their setup of hardware and software which makes transferring a visualisation application from one high-resolution system to another one a complicated task. As more and more such visualisation systems get installed, collaboration becomes desirable in the sense of sharing such a visualisation running on one site in real time with another highresolution display on a remote site while at the same time communicating via video and audio. Since typical video conference solutions or web-based collaboration tools often cannot deal with resolutions exceeding 4K, with stereo displays or with multi- GPU setups, we designed and implemented a new system based on state-of-the-art hardware and software technologies to transmit high-resolution visualisations including video and audio streams via the internet to remote large displays and back. Our system architecture is built on efficient capturing, encoding and transmission of pixel streams and thus supports a multitude of configurations combining audio and video streams in a generic approach.
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    Segmenting Computer-Tomographic Scans of Ancient Clay Artefacts for Visual Analysis of Cuneiform Inscriptions
    (The Eurographics Association, 2020) Rolff, Tim; Rautenhaus, Marc; Olbrich, Stephan; Frintrop, Simone; Krüger, Jens and Niessner, Matthias and Stückler, Jörg
    We address the automatic segmentation of computer tomographic scans of ancient clay tablets with cuneiform inscriptions enclosed inside a clay envelope. Such separation of parts of similar material properties in the scan enables domain scientists to virtually investigate the historically valuable artefacts by means of 3D visualization without physical destruction.We investigate two segmentation methods, the Priority-Flood algorithm and the Compact Watershed algorithm, the latter being modified by employing a distance metric that takes the ellipsoidal shape of the artefacts into account. Additionally, we propose a novel presegmentation method that suppresses the intensity values of the distance transform at contact points between clay envelope and tablet. We apply all methods to volumetric scans of a replicated clay tablet and analyze their performance under varying noise distributions. Evaluation by comparison to a manually segmented ground truth shows best results for the novel suppressionbased approach.
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    WLD: A Wavelet and Learning based Line Descriptor for Line Feature Matching
    (The Eurographics Association, 2020) Lange, Manuel; Raisch, Claudio; Schilling, Andreas; Krüger, Jens and Niessner, Matthias and Stückler, Jörg
    We present a machine learning based and wavelet enhanced line feature descriptor for line feature matching. Therefor we trained a neural network to compute a descriptor for a line, given preprocessed information from the image area around the line. In the preprocessing step we utilize wavelets to extract meaningful information from the image for the descriptor. This process is inspired by the human vision system. We used the Unreal Engine 4 and multiple different freely available scenes to create our training data. We conducted the evaluation on ground truth labeled images of our own and from the Middlebury Stereo Dataset. To show the advancement of our method in terms of matching quality, we compare it to the Line Band Descriptor (LBD), to the Deep Learning Based Line Descriptor (DLD), which we used as a starting point for this work, and to the Learnable Line Segment Descriptor for Visual SLAM (LLD). We publish the project on github to support the community: https://github.com/manuellange/WLD