Material Recognition Meets 3D Reconstruction : Novel Tools for Efficient, Automatic Acquisition Systems

For decades, the accurate acquisition of geometry and reflectance properties has represented one of the major objectives in computer vision and computer graphics with many applications in industry, entertainment and cultural heritage. Reproducing even the finest details of surface geometry and surface reflectance has become a ubiquitous prerequisite in visual prototyping, advertisement or digital preservation of objects. However, today's acquisition methods are typically designed for only a rather small range of material types. Furthermore, there is still a lack of accurate reconstruction methods for objects with a more complex surface reflectance behavior beyond diffuse reflectance. In addition to accurate acquisition techniques, the demand for creating large quantities of digital contents also pushes the focus towards fully automatic and highly efficient solutions that allow for masses of objects to be acquired as fast as possible. This thesis is dedicated to the investigation of basic components that allow an efficient, automatic acquisition process. We argue that such an efficient, automatic acquisition can be realized when material recognition "meets" 3D reconstruction and we will demonstrate that reliably recognizing the materials of the considered object allows a more efficient geometry acquisition. Therefore, the main objectives of this thesis are given by the development of novel, robust geometry acquisition techniques for surface materials beyond diffuse surface reflectance, and the development of novel, robust techniques for material recognition. In the context of 3D geometry acquisition, we introduce an improvement of structured light systems, which are capable of robustly acquiring objects ranging from diffuse surface reflectance to even specular surface reflectance with a sufficient diffuse component. We demonstrate that the resolution of the reconstruction can be increased significantly for multi-camera, multi-projector structured light systems by using overlappings of patterns that have been projected under different projector poses. As the reconstructions obtained by applying such triangulation-based techniques still contain high-frequency noise due to inaccurately localized correspondences established for images acquired under different viewpoints, we furthermore introduce a novel geometry acquisition technique that complements the structured light system with additional photometric normals and results in significantly more accurate reconstructions. In addition, we also present a novel method to acquire the 3D shape of mirroring objects with complex surface geometry. The aforementioned investigations on 3D reconstruction are accompanied by the development of novel tools for reliable material recognition which can be used in an initial step to recognize the present surface materials and, hence, to efficiently select the subsequently applied appropriate acquisition techniques based on these classified materials. In the scope of this thesis, we therefore focus on material recognition for scenarios with controlled illumination as given in lab environments as well as scenarios with natural illumination that are given in photographs of typical daily life scenes. Finally, based on the techniques developed in this thesis, we provide novel concepts towards efficient, automatic acquisition systems

Communication of Digital Material Appearance Based on Human Perception

Im alltägliche Leben begegnen wir digitalen Materialien in einer Vielzahl von Situationen wie beispielsweise bei Computerspielen, Filmen, Reklamewänden in zB U-Bahn Stationen oder beim Online-Kauf von Kleidungen. Während einige dieser Materialien durch digitale Modelle repräsentiert werden, welche das Aussehen einer bestimmten Oberfläche in Abhängigkeit des Materials der Fläche sowie den Beleuchtungsbedingungen beschreiben, basieren andere digitale Darstellungen auf der simplen Verwendung von Fotos der realen Materialien, was zB bei Online-Shopping häufig verwendet wird. Die Verwendung von computer-generierten Materialien ist im Vergleich zu einzelnen Fotos besonders vorteilhaft, da diese realistische Erfahrungen im Rahmen von virtuellen Szenarien, kooperativem Produkt-Design, Marketing während der prototypischen Entwicklungsphase oder der Ausstellung von Möbeln oder Accesoires in spezifischen Umgebungen erlauben. Während mittels aktueller Digitalisierungsmethoden bereits eine beeindruckende Reproduktionsqualität erzielt wird, wird eine hochpräzise photorealistische digitale Reproduktion von Materialien für die große Vielfalt von Materialtypen nicht erreicht. Daher verwenden viele Materialkataloge immer noch Fotos oder sogar physikalische Materialproben um ihre Kollektionen zu repräsentieren. Ein wichtiger Grund für diese Lücke in der Genauigkeit des Aussehens von digitalen zu echten Materialien liegt darin, dass die Zusammenhänge zwischen physikalischen Materialeigenschaften und der vom Menschen wahrgenommenen visuellen Qualität noch weitgehend unbekannt sind. Die im Rahmen dieser Arbeit durchgeführten Untersuchungen adressieren diesen Aspekt. Zu diesem Zweck werden etablierte digitalie Materialmodellen bezüglich ihrer Eignung zur Kommunikation von physikalischen und sujektiven Materialeigenschaften untersucht, wobei Beobachtungen darauf hinweisen, dass ein Teil der fühlbaren/haptischen Informationen wie z.B. Materialstärke oder Härtegrad aufgrund der dem Modell anhaftenden geometrische Abstraktion verloren gehen. Folglich wird im Rahmen der Arbeit das Zusammenspiel der verschiedenen Sinneswahrnehmungen (mit Fokus auf die visuellen und akustischen Modalitäten) untersucht um festzustellen, welche Informationen während des Digitalisierungsprozesses verloren gehen. Es zeigt sich, dass insbesondere akustische Informationen in Kombination mit der visuellen Wahrnehmung die Einschätzung fühlbarer Materialeigenschaften erleichtert. Eines der Defizite bei der Analyse des Aussehens von Materialien ist der Mangel bezüglich sich an der Wahnehmung richtenden Metriken die eine Beantwortung von Fragen wie z.B. "Sind die Materialien A und B sich ähnlicher als die Materialien C und D?" erlauben, wie sie in vielen Anwendungen der Computergrafik auftreten. Daher widmen sich die im Rahmen dieser Arbeit durchgeführten Studien auch dem Vergleich von unterschiedlichen Materialrepräsentationen im Hinblick auf. Zu diesem Zweck wird eine Methodik zur Berechnung der wahrgenommenen paarweisen Ähnlichkeit von Material-Texturen eingeführt, welche auf der Verwendung von Textursyntheseverfahren beruht und sich an der Idee/dem Begriff der geradenoch-wahrnehmbaren Unterschiede orientiert. Der vorgeschlagene Ansatz erlaubt das Überwinden einiger Probleme zuvor veröffentlichter Methoden zur Bestimmung der Änhlichkeit von Texturen und führt zu sinnvollen/plausiblen Distanzen von Materialprobem. Zusammenfassend führen die im Rahmen dieser Dissertation dargestellten Inhalte/Verfahren zu einem tieferen Verständnis bezüglich der menschlichen Wahnehmung von digitalen bzw. realen Materialien über unterschiedliche Sinne, einem besseren Verständnis bzgl. der Bewertung der Ähnlichkeit von Texturen durch die Entwicklung einer neuen perzeptuellen Metrik und liefern grundlegende Einsichten für zukünftige Untersuchungen im Bereich der Perzeption von digitalen Materialien.In daily life, we encounter digital materials and interact with them in numerous situations, for instance when we play computer games, watch a movie, see billboard in the metro station or buy new clothes online. While some of these virtual materials are given by computational models that describe the appearance of a particular surface based on its material and the illumination conditions, some others are presented as simple digital photographs of real materials, as is usually the case for material samples from online retailing stores. The utilization of computer-generated materials entails significant advantages over plain images as they allow realistic experiences in virtual scenarios, cooperative product design, advertising in prototype phase or exhibition of furniture and wearables in specific environments. However, even though exceptional material reproduction quality has been achieved in the domain of computer graphics, current technology is still far away from highly accurate photo-realistic virtual material reproductions for the wide range of existing categories and, for this reason, many material catalogs still use pictures or even physical material samples to illustrate their collections. An important reason for this gap between digital and real material appearance is that the connections between physical material characteristics and the visual quality perceived by humans are far from well-understood. Our investigations intend to shed some light in this direction. Concretely, we explore the ability of state-of-the-art digital material models in communicating physical and subjective material qualities, observing that part of the tactile/haptic information (eg thickness, hardness) is missing due to the geometric abstractions intrinsic to the model. Consequently, in order to account for the information deteriorated during the digitization process, we investigate the interplay between different sensing modalities (vision and hearing) and discover that particular sound cues, in combination with visual information, facilitate the estimation of such tactile material qualities. One of the shortcomings when studying material appearance is the lack of perceptually-derived metrics able to answer questions like "are materials A and B more similar than C and D?", which arise in many computer graphics applications. In the absence of such metrics, our studies compare different appearance models in terms of how capable are they to depict/transmit a collection of meaningful perceptual qualities. To address this problem, we introduce a methodology to compute the perceived pairwise similarity between textures from material samples that makes use of patch-based texture synthesis algorithms and is inspired on the notion of Just-Noticeable Differences. Our technique is able to overcome some of the issues posed by previous texture similarity collection methods and produces meaningful distances between samples. In summary, with the contents presented in this thesis we are able to delve deeply in how humans perceive digital and real materials through different senses, acquire a better understanding of texture similarity by developing a perceptually-based metric and provide a groundwork for further investigations in the perception of digital materials

Untersuchungen zur Detektion von spekulären Reflexionen in Fassadenbildern

Schlagschatten und Spiegelungen zeigen den Einfluss von direkter Beleuchtung während der Bildgewinnung und damit die Notwendigkeit, sie bei der Bildanalyse zu berücksichtigen. Bei der Visualisierung virtueller Welten kommen Beleuchtungsmodelle zum Einsatz, wie z.B. das Modell von Phong (1975), bei dem zwischen diffuser Streuung des Lichts und spekulären Reflexionen unterschieden wird. Im vorgelegten Beitrag werden zwei bestehende Ansätze für die Detektion von spekulären Reflexionen vorgestellt, und es wird untersucht, ob diese nicht nur unter Laborbedingungen, sondern bei der Analyse von Fassadenbildern eingesetzt werden können. Es wird gezeigt, dass selbst unter Hinzunahme weiterer Information wie die 3D-Geometrie der Szene, d.h. des rekonstruierten Objekts und der Lokalisierung einer potentiellen Lichtquelle in einer Richtungskugel, helle, diffuse Streuung die Detektion spekulärer Reflexionen stark behindert

Towards Predictive Rendering in Virtual Reality

The strive for generating predictive images, i.e., images representing radiometrically correct renditions of reality, has been a longstanding problem in computer graphics. The exactness of such images is extremely important for Virtual Reality applications like Virtual Prototyping, where users need to make decisions impacting large investments based on the simulated images. Unfortunately, generation of predictive imagery is still an unsolved problem due to manifold reasons, especially if real-time restrictions apply. First, existing scenes used for rendering are not modeled accurately enough to create predictive images. Second, even with huge computational efforts existing rendering algorithms are not able to produce radiometrically correct images. Third, current display devices need to convert rendered images into some low-dimensional color space, which prohibits display of radiometrically correct images. Overcoming these limitations is the focus of current state-of-the-art research. This thesis also contributes to this task. First, it briefly introduces the necessary background and identifies the steps required for real-time predictive image generation. Then, existing techniques targeting these steps are presented and their limitations are pointed out. To solve some of the remaining problems, novel techniques are proposed. They cover various steps in the predictive image generation process, ranging from accurate scene modeling over efficient data representation to high-quality, real-time rendering. A special focus of this thesis lays on real-time generation of predictive images using bidirectional texture functions (BTFs), i.e., very accurate representations for spatially varying surface materials. The techniques proposed by this thesis enable efficient handling of BTFs by compressing the huge amount of data contained in this material representation, applying them to geometric surfaces using texture and BTF synthesis techniques, and rendering BTF covered objects in real-time. Further approaches proposed in this thesis target inclusion of real-time global illumination effects or more efficient rendering using novel level-of-detail representations for geometric objects. Finally, this thesis assesses the rendering quality achievable with BTF materials, indicating a significant increase in realism but also confirming the remainder of problems to be solved to achieve truly predictive image generation

FOSS4G 2016 Proceedings: Academic Program - selected papers and posters

This Conference Proceedings is a collection of selected papers and posters submitted to the Academic Program of the International Conference for Free and Open Source Software for Geospatial (FOSS4G 2016), 24th to 26th August 2016 in Bonn, Germany. Like in previous FOSS4G conferences on national and international level the academic papers and posters cover an extensive wide range of topics reflecting the contribution of the academia to this field by the development of open source software components, in the design of open standards, in the proliferation of web-based solutions, in the dissemination of the open principles important in science and education, or in the collection and the hosting of freely available geo-data

Revealing the Invisible: On the Extraction of Latent Information from Generalized Image Data

The desire to reveal the invisible in order to explain the world around us has been a source of impetus for technological and scientific progress throughout human history. Many of the phenomena that directly affect us cannot be sufficiently explained based on the observations using our primary senses alone. Often this is because their originating cause is either too small, too far away, or in other ways obstructed. To put it in other words: it is invisible to us. Without careful observation and experimentation, our models of the world remain inaccurate and research has to be conducted in order to improve our understanding of even the most basic effects. In this thesis, we1 are going to present our solutions to three challenging problems in visual computing, where a surprising amount of information is hidden in generalized image data and cannot easily be extracted by human observation or existing methods. We are able to extract the latent information using non-linear and discrete optimization methods based on physically motivated models and computer graphics methodology, such as ray tracing, real-time transient rendering, and image-based rendering

On the popularization of digital close-range photogrammetry: a handbook for new users.

Εθνικό Μετσόβιο Πολυτεχνείο--Μεταπτυχιακή Εργασία. Διεπιστημονικό-Διατμηματικό Πρόγραμμα Μεταπτυχιακών Σπουδών (Δ.Π.Μ.Σ.) “Γεωπληροφορική

Materializing interaction

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, February 2013.Cataloged from PDF version of thesis. "September 2012."Includes bibliographical references (p. 141-148).At the boundary between people, objects and spaces, we encounter a broad range of surfaces. Their properties perform functional roles such as permeability, comfort or illumination, while conveying information such as an object's affordances, composition, or history of use. However, today surfaces are static and can neither adapt to our changing needs, nor communicate dynamic information and sense user input. As technology advances and we progress towards a world imbued with programmable materials, how will designers create physical surfaces that are adaptive and can take full advantage of our sensory apparatus? This dissertation looks at this question through the lens of a three-tier methodology consisting of the development of programmable composites; their application in design and architecture; and contextualization through a broader material and surface taxonomy. The focus is placed primarily on how materials and their aggregate surface properties can be used to engage our senses. A series of design probes and four final implementations are presented, each addressing specific programmable material and surface properties. Surflex, Sprout 1/O, and Shutters are continuous surfaces which can change shape to modify their topology, texture and permeability, and Six-Forty by Four-Eighty is a light-emitting display surface composed of autonomous and reconfigurable physical pixels. The technical and conceptual objectives of these designs are evaluated through exhibitions in a variety of public spaces, such as museums, galleries, fairs, as well as art and design festivals. This dissertation seeks to provide contributions on multiple levels, including: the development of techniques for the creation and control of programmable surfaces; the definition of a vocabulary and taxonomy to describe and compare previous work in this area; and finally, uncovering design principles for the underlying development of future programmable surface aesthetics.by Marcelo Coelho.Ph.D