Algorithmen zur Korrespondenzschätzung und Bildinterpolation für die photorealistische Bildsynthese

Free-viewpoint video is a new form of visual medium that has received considerable attention in the last 10 years. Most systems reconstruct the geometry of the scene, thus restricting themselves to synchronized multi-view footage and Lambertian scenes. In this thesis we follow a different approach and describe contributions to a purely image-based end-to-end system operating on sparse, unsynchronized multi-view footage. In particular, we focus on dense correspondence estimation and synthesis of in-between views. In contrast to previous approaches, our correspondence estimation is specifically tailored to the needs of image interpolation; our multi-image interpolation technique advances the state-of-the-art by disposing the conventional blending step. Both algorithms are put to work in an image-based free-viewpoint video system and we demonstrate their applicability to space-time visual effects production as well as to stereoscopic content creation.3D-Video mit Blickpunktnavigation ist eine neues digitales Medium welchem die Forschung in den letzten 10 Jahren viel Aufmerksamkeit gewidmet hat. Die meisten Verfahren rekonstruieren dabei die Szenengeometrie und schränken sich somit auf Lambertsche Szenen und synchron aufgenommene Eingabedaten ein. In dieser Dissertation beschreiben wir Beiträge zu einem rein bild-basierten System welches auf unsynchronisierten Eingabevideos arbeitet. Unser Fokus liegt dabei auf der Schätzung dichter Korrespondenzkarten und auf der Synthese von Zwischenbildern. Im Gegensatz zu bisherigen Verfahren ist unser Ansatz der Korrespondenzschätzung auf die Bedürfnisse der Bilderinterpolation ausgerichtet; unsere Zwischenbildsynthese verzichtet auf das Überblenden der Eingabebilder zu Gunsten der Lösung eines Labelingproblems. Das resultierende System eignet sich sowohl zur Produktion räumlich-zeitlicher Spezialeffekte als auch zur Erzeugung stereoskopischer Videosequenzen

Glossy Probe Reprojection for Interactive Global Illumination

International audienceRecent rendering advances dramatically reduce the cost of global illumination. But even with hardware acceleration, complex light paths with multiple glossy interactions are still expensive; our new algorithm stores these paths in precomputed light probes and reprojects them at runtime to provide interactivity. Combined with traditional light maps for diffuse lighting our approach interactively renders all light paths in static scenes with opaque objects. Naively reprojecting probes with glossy lighting is memory-intensive, requires efficient access to the correctly reflected radiance, and exhibits problems at occlusion boundaries in glossy reflections. Our solution addresses all these issues. To minimize memory, we introduce an adaptive light probe parameterization that allocates increased resolution for shinier surfaces and regions of higher geometric complexity. To efficiently sample glossy paths, our novel gathering algorithm reprojects probe texels in a view-dependent manner using efficient reflection estimation and a fast rasterization-based search. Naive probe reprojection often sharpens glossy reflections at occlusion boundaries, due to changes in parallax. To avoid this, we split the convolution induced by the BRDF into two steps: we precompute probes using a lower material roughness and apply an adaptive bilateral filter at runtime to reproduce the original surface roughness. Combining these elements, our algorithm interactively renders complex scenes while fitting in the memory, bandwidth, and computation constraints of current hardware

Artistic Path Space Editing of Physically Based Light Transport

Die Erzeugung realistischer Bilder ist ein wichtiges Ziel der Computergrafik, mit Anwendungen u.a. in der Spielfilmindustrie, Architektur und Medizin. Die physikalisch basierte Bildsynthese, welche in letzter Zeit anwendungsübergreifend weiten Anklang findet, bedient sich der numerischen Simulation des Lichttransports entlang durch die geometrische Optik vorgegebener Ausbreitungspfade; ein Modell, welches für übliche Szenen ausreicht, Photorealismus zu erzielen. Insgesamt gesehen ist heute das computergestützte Verfassen von Bildern und Animationen mit wohlgestalteter und theoretisch fundierter Schattierung stark vereinfacht. Allerdings ist bei der praktischen Umsetzung auch die Rücksichtnahme auf Details wie die Struktur des Ausgabegeräts wichtig und z.B. das Teilproblem der effizienten physikalisch basierten Bildsynthese in partizipierenden Medien ist noch weit davon entfernt, als gelöst zu gelten. Weiterhin ist die Bildsynthese als Teil eines weiteren Kontextes zu sehen: der effektiven Kommunikation von Ideen und Informationen. Seien es nun Form und Funktion eines Gebäudes, die medizinische Visualisierung einer Computertomografie oder aber die Stimmung einer Filmsequenz -- Botschaften in Form digitaler Bilder sind heutzutage omnipräsent. Leider hat die Verbreitung der -- auf Simulation ausgelegten -- Methodik der physikalisch basierten Bildsynthese generell zu einem Verlust intuitiver, feingestalteter und lokaler künstlerischer Kontrolle des finalen Bildinhalts geführt, welche in vorherigen, weniger strikten Paradigmen vorhanden war. Die Beiträge dieser Dissertation decken unterschiedliche Aspekte der Bildsynthese ab. Dies sind zunächst einmal die grundlegende Subpixel-Bildsynthese sowie effiziente Bildsyntheseverfahren für partizipierende Medien. Im Mittelpunkt der Arbeit stehen jedoch Ansätze zum effektiven visuellen Verständnis der Lichtausbreitung, die eine lokale künstlerische Einflussnahme ermöglichen und gleichzeitig auf globaler Ebene konsistente und glaubwürdige Ergebnisse erzielen. Hierbei ist die Kernidee, Visualisierung und Bearbeitung des Lichts direkt im alle möglichen Lichtpfade einschließenden "Pfadraum" durchzuführen. Dies steht im Gegensatz zu Verfahren nach Stand der Forschung, die entweder im Bildraum arbeiten oder auf bestimmte, isolierte Beleuchtungseffekte wie perfekte Spiegelungen, Schatten oder Kaustiken zugeschnitten sind. Die Erprobung der vorgestellten Verfahren hat gezeigt, dass mit ihnen real existierende Probleme der Bilderzeugung für Filmproduktionen gelöst werden können

The delta radiance field

The wide availability of mobile devices capable of computing high fidelity graphics in real-time has sparked a renewed interest in the development and research of Augmented Reality applications. Within the large spectrum of mixed real and virtual elements one specific area is dedicated to produce realistic augmentations with the aim of presenting virtual copies of real existing objects or soon to be produced products. Surprisingly though, the current state of this area leaves much to be desired: Augmenting objects in current systems are often presented without any reconstructed lighting whatsoever and therefore transfer an impression of being glued over a camera image rather than augmenting reality. In light of the advances in the movie industry, which has handled cases of mixed realities from one extreme end to another, it is a legitimate question to ask why such advances did not fully reflect onto Augmented Reality simulations as well. Generally understood to be real-time applications which reconstruct the spatial relation of real world elements and virtual objects, Augmented Reality has to deal with several uncertainties. Among them, unknown illumination and real scene conditions are the most important. Any kind of reconstruction of real world properties in an ad-hoc manner must likewise be incorporated into an algorithm responsible for shading virtual objects and transferring virtual light to real surfaces in an ad-hoc fashion. The immersiveness of an Augmented Reality simulation is, next to its realism and accuracy, primarily dependent on its responsiveness. Any computation affecting the final image must be computed in real-time. This condition rules out many of the methods used for movie production. The remaining real-time options face three problems: The shading of virtual surfaces under real natural illumination, the relighting of real surfaces according to the change in illumination due to the introduction of a new object into a scene, and the believable global interaction of real and virtual light. This dissertation presents contributions to answer the problems at hand. Current state-of-the-art methods build on Differential Rendering techniques to fuse global illumination algorithms into AR environments. This simple approach has a computationally costly downside, which limits the options for believable light transfer even further. This dissertation explores new shading and relighting algorithms built on a mathematical foundation replacing Differential Rendering. The result not only presents a more efficient competitor to the current state-of-the-art in global illumination relighting, but also advances the field with the ability to simulate effects which have not been demonstrated by contemporary publications until now

Visibility computation through image generalization

This dissertation introduces the image generalization paradigm for computing visibility. The paradigm is based on the observation that an image is a powerful tool for computing visibility. An image can be rendered efficiently with the support of graphics hardware and each of the millions of pixels in the image reports a visible geometric primitive. However, the visibility solution computed by a conventional image is far from complete. A conventional image has a uniform sampling rate which can miss visible geometric primitives with a small screen footprint. A conventional image can only find geometric primitives to which there is direct line of sight from the center of projection (i.e. the eye) of the image; therefore, a conventional image cannot compute the set of geometric primitives that become visible as the viewpoint translates, or as time changes in a dynamic dataset. Finally, like any sample-based representation, a conventional image can only confirm that a geometric primitive is visible, but it cannot confirm that a geometric primitive is hidden, as that would require an infinite number of samples to confirm that the primitive is hidden at all of its points. ^ The image generalization paradigm overcomes the visibility computation limitations of conventional images. The paradigm has three elements. (1) Sampling pattern generalization entails adding sampling locations to the image plane where needed to find visible geometric primitives with a small footprint. (2) Visibility sample generalization entails replacing the conventional scalar visibility sample with a higher dimensional sample that records all geometric primitives visible at a sampling location as the viewpoint translates or as time changes in a dynamic dataset; the higher-dimensional visibility sample is computed exactly, by solving visibility event equations, and not through sampling. Another form of visibility sample generalization is to enhance a sample with its trajectory as the geometric primitive it samples moves in a dynamic dataset. (3) Ray geometry generalization redefines a camera ray as the set of 3D points that project at a given image location; this generalization supports rays that are not straight lines, and enables designing cameras with non-linear rays that circumvent occluders to gather samples not visible from a reference viewpoint. ^ The image generalization paradigm has been used to develop visibility algorithms for a variety of datasets, of visibility parameter domains, and of performance-accuracy tradeoff requirements. These include an aggressive from-point visibility algorithm that guarantees finding all geometric primitives with a visible fragment, no matter how small primitive\u27s image footprint, an efficient and robust exact from-point visibility algorithm that iterates between a sample-based and a continuous visibility analysis of the image plane to quickly converge to the exact solution, a from-rectangle visibility algorithm that uses 2D visibility samples to compute a visible set that is exact under viewpoint translation, a flexible pinhole camera that enables local modulations of the sampling rate over the image plane according to an input importance map, an animated depth image that not only stores color and depth per pixel but also a compact representation of pixel sample trajectories, and a curved ray camera that integrates seamlessly multiple viewpoints into a multiperspective image without the viewpoint transition distortion artifacts of prior art methods

Online learning of physics during a pandemic: A report from an academic experience in Italy

The arrival of the Sars-Cov II has opened a new window on teaching physics in academia. Frontal lectures have left space for online teaching, teachers have been faced with a new way of spreading knowledge, adapting contents and modalities of their courses. Students have faced up with a new way of learning physics, which relies on free access to materials and their informatics knowledge. We decided to investigate how online didactics has influenced students’ assessments, motivation, and satisfaction in learning physics during the pandemic in 2020. The research has involved bachelor (n = 53) and master (n = 27) students of the Physics Department at the University of Cagliari (N = 80, 47 male; 33 female). The MANOVA supported significant mean differences about gender and university level with higher values for girls and master students in almost all variables investigated. The path analysis showed that student-student, student-teacher interaction, and the organization of the courses significantly influenced satisfaction and motivation in learning physics. The results of this study can be used to improve the standards of teaching in physics at the University of Cagliar

New Development of Neutrosophic Probability, Neutrosophic Statistics, Neutrosophic Algebraic Structures, and Neutrosophic & Plithogenic Optimizations

This Special Issue puts forward for discussion state-of-the-art papers on new topics related to neutrosophic theories, such as neutrosophic algebraic structures, neutrosophic triplet algebraic structures, neutrosophic extended triplet algebraic structures, neutrosophic algebraic hyperstructures, neutrosophic triplet algebraic hyperstructures, neutrosophic n-ary algebraic structures, neutrosophic n-ary algebraic hyperstructures, refined neutrosophic algebraic structures, refined neutrosophic algebraic hyperstructures, quadruple neutrosophic algebraic structures, refined quadruple neutrosophic algebraic structures, neutrosophic image processing, neutrosophic image classification, neutrosophic computer vision, neutrosophic machine learning, neutrosophic artificial intelligence, neutrosophic data analytics, neutrosophic deep learning, neutrosophic symmetry, and their applications in the real world. This book leads to the further advancement of the neutrosophic and plithogenic theories of NeutroAlgebra and AntiAlgebra, NeutroGeometry and AntiGeometry, Neutrosophic n-SuperHyperGraph (the most general form of graph of today), Neutrosophic Statistics, Plithogenic Logic as a generalization of MultiVariate Logic, Plithogenic Probability and Plithogenic Statistics as a generalization of MultiVariate Probability and Statistics, respectively, and presents their countless applications in our every-day world