PROCEEDINGS OF THE IEEE SPECIAL ISSUE ON APPLICATIONS OF AUGMENTED REALITY ENVIRONMENTS 1 Augmented Reality for Construction Site Monitoring and Documentation

Abstract—Augmented Reality allows for an on-site presentation of information that is registered to the physical environment. Applications from civil engineering, which require users to process complex information, are among those which can benefit particularly highly from such a presentation. In this paper, we will describe how to use Augmented Reality (AR) to support monitoring and documentation of construction site progress. For these tasks, the staff responsible usually requires fast and comprehensible access to progress information to enable comparison to the as-built status as well as to as-planned data. Instead of tediously searching and mapping related information to the actual construction site environment, our AR system allows for the access of information right where it is needed. This is achieved by superimposing progress as well as as-planned information onto the user’s view of the physical environment. For this purpose, we present an approach that uses aerial 3D reconstruction to automatically capture progress information and a mobile AR client for on-site visualization. Within this paper, we will describe in greater detail how to capture 3D, how to register the AR system within the physical outdoor environment, how to visualize progress information in a comprehensible way in an AR overlay and how to interact with this kind of information. By implementing such an AR system, we are able to provide an overview about the possibilities and future applications of AR in the construction industry

Efficient image-based rendering

Recent advancements in real-time ray tracing and deep learning have significantly enhanced the realism of computer-generated images. However, conventional 3D computer graphics (CG) can still be time-consuming and resource-intensive, particularly when creating photo-realistic simulations of complex or animated scenes. Image-based rendering (IBR) has emerged as an alternative approach that utilizes pre-captured images from the real world to generate realistic images in real-time, eliminating the need for extensive modeling. Although IBR has its advantages, it faces challenges in providing the same level of control over scene attributes as traditional CG pipelines and accurately reproducing complex scenes and objects with different materials, such as transparent objects. This thesis endeavors to address these issues by harnessing the power of deep learning and incorporating the fundamental principles of graphics and physical-based rendering. It offers an efficient solution that enables interactive manipulation of real-world dynamic scenes captured from sparse views, lighting positions, and times, as well as a physically-based approach that facilitates accurate reproduction of the view dependency effect resulting from the interaction between transparent objects and their surrounding environment. Additionally, this thesis develops a visibility metric that can identify artifacts in the reconstructed IBR images without observing the reference image, thereby contributing to the design of an effective IBR acquisition pipeline. Lastly, a perception-driven rendering technique is developed to provide high-fidelity visual content in virtual reality displays while retaining computational efficiency.Jüngste Fortschritte im Bereich Echtzeit-Raytracing und Deep Learning haben den Realismus computergenerierter Bilder erheblich verbessert. Konventionelle 3DComputergrafik (CG) kann jedoch nach wie vor zeit- und ressourcenintensiv sein, insbesondere bei der Erstellung fotorealistischer Simulationen von komplexen oder animierten Szenen. Das bildbasierte Rendering (IBR) hat sich als alternativer Ansatz herauskristallisiert, bei dem vorab aufgenommene Bilder aus der realen Welt verwendet werden, um realistische Bilder in Echtzeit zu erzeugen, so dass keine umfangreiche Modellierung erforderlich ist. Obwohl IBR seine Vorteile hat, ist es eine Herausforderung, das gleiche Maß an Kontrolle über Szenenattribute zu bieten wie traditionelle CG-Pipelines und komplexe Szenen und Objekte mit unterschiedlichen Materialien, wie z.B. transparente Objekte, akkurat wiederzugeben. In dieser Arbeit wird versucht, diese Probleme zu lösen, indem die Möglichkeiten des Deep Learning genutzt und die grundlegenden Prinzipien der Grafik und des physikalisch basierten Renderings einbezogen werden. Sie bietet eine effiziente Lösung, die eine interaktive Manipulation von dynamischen Szenen aus der realen Welt ermöglicht, die aus spärlichen Ansichten, Beleuchtungspositionen und Zeiten erfasst wurden, sowie einen physikalisch basierten Ansatz, der eine genaue Reproduktion des Effekts der Sichtabhängigkeit ermöglicht, der sich aus der Interaktion zwischen transparenten Objekten und ihrer Umgebung ergibt. Darüber hinaus wird in dieser Arbeit eine Sichtbarkeitsmetrik entwickelt, mit der Artefakte in den rekonstruierten IBR-Bildern identifiziert werden können, ohne das Referenzbild zu betrachten, und die somit zur Entwicklung einer effektiven IBR-Erfassungspipeline beiträgt. Schließlich wird ein wahrnehmungsgesteuertes Rendering-Verfahren entwickelt, um visuelle Inhalte in Virtual-Reality-Displays mit hoherWiedergabetreue zu liefern und gleichzeitig die Rechenleistung zu erhalten

Analysis domain model for shared virtual environments

The field of shared virtual environments, which also encompasses online games and social 3D environments, has a system landscape consisting of multiple solutions that share great functional overlap. However, there is little system interoperability between the different solutions. A shared virtual environment has an associated problem domain that is highly complex raising difficult challenges to the development process, starting with the architectural design of the underlying system. This paper has two main contributions. The first contribution is a broad domain analysis of shared virtual environments, which enables developers to have a better understanding of the whole rather than the part(s). The second contribution is a reference domain model for discussing and describing solutions - the Analysis Domain Model

Gradient Domain Methods for Image-based Reconstruction and Rendering

This thesis describes new approaches in image-based 3D reconstruction and rendering. In contrast to previous work our algorithms focus on image gradients instead of pixel values which allows us to avoid many of the disadvantages traditional techniques have. A single pixel only carries very local information about the image content. A gradient on the other hand reveals information about the magnitude and the direction in which the image content changes. Our techniques use this additional information to adapt dynamically to the image content. Especially in image regions without strong gradients we can employ more suitable reconstruction models and we can render images with less artifacts. Overall we present more accurate and robust results (both 3D models and renderings) compared to previous methods. First, we present a multi-view stereo algorithm that combines traditional stereo reconstruction and shading based reconstruction models in a single optimization scheme. By defining as gradient based trade off our model removes the need for an explicit regularization and can handle shading information without the need for an explicit albedo model. This effectively combines the strength of both reconstruction approaches and cancels out their weaknesses. Our second method is an image-based rendering technique that directly renders gradients instead of pixels. The final image is then generated by integrating over the rendered gradients. We present a detailed description on how gradients can be moved directly in the image during rendering which allows us to create a fast approximation that improves the quality and speed of the integration step. Our method also handles occlusions and compared to traditional approaches we can achieve better results that are especially robust for scenes with reflective or textureless areas. Finally, we also present a new model for image warping. Here we apply different types of regularization constraints based on the gradients in the image. Especially when used for direct real-time rendering this can handle larger distortions compared to traditional methods that use only a single type of regularization. Overall the results of this thesis show how shifting the focus from image pixels to image gradients can improve various aspects of image-based reconstruction and rendering. Some of the most challenging aspects such as textureless areas in rendering and spatially varying albedo in reconstruction are handled implicitly by our formulations which also leads to more effective algorithms

Synthesizing and Editing Photo-realistic Visual Objects

In this thesis we investigate novel methods of synthesizing new images of a deformable visual object using a collection of images of the object. We investigate both parametric and non-parametric methods as well as a combination of the two methods for the problem of image synthesis. Our main focus are complex visual objects, specifically deformable objects and objects with varying numbers of visible parts. We first introduce sketch-driven image synthesis system, which allows the user to draw ellipses and outlines in order to sketch a rough shape of animals as a constraint to the synthesized image. This system interactively provides feedback in the form of ellipse and contour suggestions to the partial sketch of the user. The user's sketch guides the non-parametric synthesis algorithm that blends patches from two exemplar images in a coarse-to-fine fashion to create a final image. We evaluate the method and synthesized images through two user studies. Instead of non-parametric blending of patches, a parametric model of the appearance is more desirable as its appearance representation is shared between all images of the dataset. Hence, we propose Context-Conditioned Component Analysis, a probabilistic generative parametric model, which described images with a linear combination of basis functions. The basis functions are evaluated for each pixel using a context vector computed from the local shape information. We evaluate C-CCA qualitatively and quantitatively on inpainting, appearance transfer and reconstruction tasks. Drawing samples of C-CCA generates novel, globally-coherent images, which, unfortunately, lack high-frequency details due to dimensionality reduction and misalignment. We develop a non-parametric model that enhances the samples of C-CCA with locally-coherent, high-frequency details. The non-parametric model efficiently finds patches from the dataset that match the C-CCA sample and blends the patches together. We analyze the results of the combined method on the datasets of horse and elephant images

Task-based Adaptation of Graphical Content in Smart Visual Interfaces

To be effective visual representations must be adapted to their respective context of use, especially in so-called Smart Visual Interfaces striving to present specifically those information required for the task at hand. This thesis proposes a generic approach that facilitate the automatic generation of task-specific visual representations from suitable task descriptions. It is discussed how the approach is applied to four principal content types raster images, 2D vector and 3D graphics as well as data visualizations, and how existing display techniques can be integrated into the approach.Effektive visuelle Repräsentationen müssen an den jeweiligen Nutzungskontext angepasst sein, insbesondere in sog. Smart Visual Interfaces, welche anstreben, möglichst genau für die aktuelle Aufgabe benötigte Informationen anzubieten. Diese Arbeit entwirft einen generischen Ansatz zur automatischen Erzeugung aufgabenspezifischer Darstellungen anhand geeigneter Aufgabenbeschreibungen. Es wird gezeigt, wie dieser Ansatz auf vier grundlegende Inhaltstypen Rasterbilder, 2D-Vektor- und 3D-Grafik sowie Datenvisualisierungen anwendbar ist, und wie existierende Darstellungstechniken integrierbar sind

The People Inside

Our collection begins with an example of computer vision that cuts through time and bureaucratic opacity to help us meet real people from the past. Buried in thousands of files in the National Archives of Australia is evidence of the exclusionary “White Australia” policies of the nineteenth and twentieth centuries, which were intended to limit and discourage immigration by non-Europeans. Tim Sherratt and Kate Bagnall decided to see what would happen if they used a form of face-detection software made ubiquitous by modern surveillance systems and applied it to a security system of a century ago. What we get is a new way to see the government documents, not as a source of statistics but, Sherratt and Bagnall argue, as powerful evidence of the people affected by racism

Exploring Sparse, Unstructured Video Collections of Places

The abundance of mobile devices and digital cameras with video capture makes it easy to obtain large collections of video clips that contain the same location, environment, or event. However, such an unstructured collection is difficult to comprehend and explore. We propose a system that analyses collections of unstructured but related video data to create a Videoscape: a data structure that enables interactive exploration of video collections by visually navigating — spatially and/or temporally — between different clips. We automatically identify transition opportunities, or portals. From these portals, we construct the Videoscape, a graph whose edges are video clips and whose nodes are portals between clips. Now structured, the videos can be interactively explored by walking the graph or by geographic map. Given this system, we gauge preference for different video transition styles in a user study, and generate heuristics that automatically choose an appropriate transition style. We evaluate our system using three further user studies, which allows us to conclude that Videoscapes provides significant benefits over related methods. Our system leads to previously unseen ways of interactive spatio-temporal exploration of casually captured videos, and we demonstrate this on several video collections

Drawing Futures

Drawing Futures brings together international designers and artists for speculations in contemporary drawing for art and architecture. Despite numerous developments in technological manufacture and computational design that provide new grounds for designers, the act of drawing still plays a central role as a vehicle for speculation. There is a rich and long history of drawing tied to innovations in technology as well as to revolutions in our philosophical understanding of the world. In reflection of a society now underpinned by computational networks and interfaces allowing hitherto unprecedented views of the world, the changing status of the drawing and its representation as a political act demands a platform for reflection and innovation. Drawing Futures will present a compendium of projects, writings and interviews that critically reassess the act of drawing and where its future may lie. Drawing Futures focuses on the discussion of how the field of drawing may expand synchronously alongside technological and computational developments. The book coincides with an international conference of the same name, taking place at The Bartlett School of Architecture, UCL, in November 2016. Bringing together practitioners from many creative fields, the book discusses how drawing is changing in relation to new technologies for the production and dissemination of ideas

Forms of Memory: The Sonnet in Contemporary British and Irish Poetry

This thesis explores the extraordinary profusion of the sonnet in contemporary British and Irish poetry, focussing in particular on the work of Geoffrey Hill, Seamus Heaney, Paul Muldoon, Don Paterson and Alice Oswald. Drawing on critical interventions by Steph Burt, who characterises the sonnet in terms of its longevity rather than any technical feature, and situating the contemporary form within the long durée of its late-eighteenth century revival (especially in Wordsworth’s work), I argue that contemporary poets have taken the sonnet up as a way of writing the past. Chapter one explores the sonnet’s fraught commemorative role in the work of Hill in the 1960s and 1970s in particular in which the form becomes a type of ‘belated witness’ to violent historical traumas. Chapter two considers Heaney, whose early sonnets are also commemorative and historical, but also increasingly, under Wordsworth’s influence, frame their commemorations in more personal, private terms, a shift that culminates in the more spiritual outlook of Heaney’s later sonnets. Chapter three focuses on Muldoon, whose relentless experiments with the sonnet mark him out as perhaps the most significant sonnet writer of the second half of the twentieth century. I read his mix of invention and obsession in relation to the form as an instance of Freudian repetition in which the past is both omnipresent and elusive. Chapter four examines Paterson, and tracks his sometimes contradictory investments in Scottish history alongside his more speculative metaphysical interests, partially derived from his translations of two crucial twentieth-century European sonneteers, Rainer Maria Rilke and Antonio Machado. The fifth and final chapter explores Oswald’s ecological commitments in sonnets marked by the influence of John Clare and Sir Thomas Wyatt. As these disparate examples indicate, the sonnet does not articulate just one past, but multiple overlapping and sometimes competing pasts