Large-scale point-cloud visualization through localized textured surface reconstruction

In this paper, we introduce a novel scene representation for the visualization of large-scale point clouds accompanied by a set of high-resolution photographs. Many real-world applications deal with very densely sampled point-cloud data, which are augmented with photographs that often reveal lighting variations and inaccuracies in registration. Consequently, the high-quality representation of the captured data, i.e., both point clouds and photographs together, is a challenging and time-consuming task. We propose a two-phase approach, in which the first (preprocessing) phase generates multiple overlapping surface patches and handles the problem of seamless texture generation locally for each patch. The second phase stitches these patches at render-time to produce a high-quality visualization of the data. As a result of the proposed localization of the global texturing problem, our algorithm is more than an order of magnitude faster than equivalent mesh-based texturing techniques. Furthermore, since our preprocessing phase requires only a minor fraction of the whole data set at once, we provide maximum flexibility when dealing with growing data sets

Cross-Modal Search and Exploration of Greek Painted Pottery

This paper focuses on digitally-supported research methods for an important group of cultural heritage objects, the Greek pottery, especially with figured decoration. The design, development and application of new digital methods for searching, comparing, and visually exploring these vases needs an interdisciplinary approach to effectively analyse the various features of the vases, like shape, decoration, and manufacturing techniques, and relationships between the vases. We motivate the need and opportunities by a multimodal representation of the objects, including 3D shape, material, and painting. We then illustrate a range of innovative methods for these representations, including quantified surface and capacity comparison, material analysis, image flattening from 3D objects, retrieval and comparison of shapes and paintings, and multidimensional data visualization. We also discuss challenges and future work in this area.Comment: 14 pages, 10 figures, preprint for a book chapter, supplementary video available at https://youtu.be/x_Xg0vy3nJ

Interactive curved reflections in large point clouds

Zsfassung in dt. SpracheIm Bereich des Echtzeitrenderings verzeichnet die Computergraphik eine immer rascher zunehmende Darstellungsfähigkeit für immer größere und komplexere Szenen. In den letzten Jahren haben sich eine Vielzahl an Rendering-Techniken etabliert, die die Qualität der generierten Bilder in konventionellen Polygonszenen immer mehr an den Fotorealismus konvergieren lässt. Vor allem im Teilbereich der realistischen Beleuchtung von Szenen stellen Global-Illumination (GI) Techniken aktuell ein wichtiges Forschungsgebiet dar. Im Vorfeld dieser Arbeit haben wir erstmals einen GI-Algorithmus auf riesige Punktwolkenszenen angewandt, mit dem wir eine realistische Beleuchtung von diffusen und glänzenden Objekten in Echtzeit erzeugen können. Die vorliegende Diplomarbeit setzt die Leistungsfähigkeit dieses GI-Renderers auf die nächste Ebene. Sie implementiert erstmals die Darstellung von Oberflächenspiegelungen auch für Punktwolkenszenen.Bisherige Echtzeit-Rendering-Techniken für gekrümmte Spiegelungen in Polygonszenen sind entweder extrem ungenau, oder unterstützen nicht jede beliebige Art von Oberfläche. Speziell konkav gekrümmte Oberflächen stellen bei aktuellen, physikalisch korrekten Ansätzen ein Problem dar.Bisher können korrekte Spiegelungen auf komplexeren Oberflächen nur durch Offline-Algorithmen erzeugt werden.Wir haben eine neuartige Technik namens "Screen-Space Curved Reflections" entwickelt, die es erlaubt, physikalisch korrekte Spiegelungen auf beliebig komplexen Oberflächen darzustellen. Die Methode basiert auf dem Ansatz, für jeden Punkt in der Szene jenen Pixel im Framebuffer zu suchen, der dessen reflektierenden Oberflächenpunkt enthält. Wir erreichen dies durch einen effizienten Gradientenabstieg auf einer von uns eingeführten Fehlerfunktion, der "mirror-space error function". Obwohl unsere Methode hohe Anforderungen an die Hardware stellt, sind wir in der Lage, gängige Szenen bei interaktiven Bildwiederholungsraten darzustellen.In the field of real-time rendering, computer graphics observes a continuously growing power of visualizing of scenes of continuously growing complexity. In the past few years, a number of rendering techniques have been developed that let the quality of the rendered images converge towards photorealism. Especially in the field of realistic scene illumination, Global Illumination (GI) techniques represent an important field of research. Previous to this work, for the first time we have applied a GI algorithm also to point clouds, which enables us to achieve realistic illumination of diffuse and glossy objects in real-time.This thesis elevates the power of visualization of this GI-Renderer to the next level. For the first time, it implements a realistic, physically based rendering of mirroring surfaces also for point clouds.Current real-time approaches addressing curved mirroring surfaces in polygon scenes either are extremely imprecise or cannot handle each arbitrary type of surface. Especially concave surfaces represent a significant difficulty for current physically based methods. Up to now, physically correct mirror reflections on complex surfaces can only be produced by offline algorithms. We introduce a novel rendering technique called "Screen-space curved reflections", which enables us to produce physically correct mirror reflections on arbitrarily complex surfaces. Our method bases on the approach, for each point in the scene to find the pixel in the framebuffer that contains its reflecting surface point. This is achieved by the application of a fast gradient descent on a new error function called "mirror-space error function". Although our method raises high demands on the hardware, we are able to render common scenes at interactive frame rates.9

Rendering of Point Clouds

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Efficient Point Cloud Skeletonization with Locally Adaptive L1-Medial Projection

3D line skeletons are simplistic representations of a shape’s topology which are used for a wide variety of geometry-processing tasks, including shape recognition, retrieval, and reconstruction. Numerous methods have been proposed to generate a skeleton from a given 3D shape. While mesh-based methods can exploit existing knowledge about the shape’s topology and orientation, point-based techniques often resort to precomputed per- point normals to ensure robustness. In contrast, previously proposed techniques for unprocessed point clouds either exhibit inferior robustness or require expensive operations, which in turn increases computation time. In this paper, we present a new and highly efficient skeletonization approach for raw point cloud data, which produces overall competitive results compared to previous work, while exhibiting much lower computation times. Our algo- rithm performs robustly in the face of noisy and fragmented inputs, as they are usually obtained from real-world 3D scans. We achieve this by first transferring the input point cloud into a Gaussian mixture model (GMM), obtaining a more compact representation of the surface. Our method then iteratively projects a small subset of the points into local L1-medians, yielding a rough outline of the shape’s skeleton. Finally, we present a new branch detection technique to obtain a coherent line skeleton from those projected points. We demonstrate the capabilities of our proposed method by extracting the line skeletons of a diverse selection of input shapes and evaluating their visual appearance as well as the efficiency compared to alternative state-of-the-art method

Thermal conduction effects on the accretion-ejection mechanism. Outflow process investigation

Astrophysical jets emanating from different systems are one of the most spectacular and enigmatic phenomena pervading the Universe. These jets are typically bipolar and span hundreds of thousands of light years, some even longer than the diameter of our Milky Way. The study of the disc-jet systems is motivated by the observed correlation between ejection and accretion signatures and is still under debate. It was shown in our previous work the crucial role of thermal conduction in the dynamics of a thin viscous resistive accretion disc orbiting a central object and was provided an unprecedented wealth of discussion that has advanced our understanding of the inflow process. In this work, we expand our exploration by addressing the most outstanding basic questions concerning the launching, acceleration, and collimation processes of the jet in presence of thermal conduction. We also tackle in depth-analysis the effects of this physical ingredient on the time evolution of temperature and on mass fluxes such as inflow and outflow rates. We performed a series of 2.5-dimensional non-relativistic time-dependent numerical calculations of a disc-jet system using the PLUTO code. Our results revealed compelling evidence that thermal conduction contributes to launching a faster and more collimated jet. The mass extracted from the disc via the outflow channel is also affected by the presence of thermal conduction in the sense that the ejection efficiency is significantly improved

Continuous projection for fast L_1 reconstruction

With better and faster acquisition devices comes a demand for fast robust reconstruction algorithms, but no L1-based technique has been fast enough for online use so far. In this paper, we present a novel continuous formulation of the weighted locally optimal projection (WLOP) operator based on a Gaussian mixture describing the input point density. Our method is up to 7 times faster than an optimized GPU implementation of WLOP, and achieves interactive frame rates for moderately sized point clouds. We give a comprehensive quality analysis showing that our continuous operator achieves a generally higher reconstruction quality than its discrete counterpart. Additionally, we show how to apply our continuous formulation to spherical mixtures of normal directions, to also achieve a fast robust normal reconstruction