BigSUR: Large-scale Structured Urban Reconstruction

The creation of high-quality semantically parsed 3D models for dense metropolitan areas is a fundamental urban modeling problem. Although recent advances in acquisition techniques and processing algorithms have resulted in large-scale imagery or 3D polygonal reconstructions, such data-sources are typically noisy, and incomplete, with no semantic structure. In this paper, we present an automatic data fusion technique that produces high-quality structured models of city blocks. From coarse polygonal meshes, street-level imagery, and GIS footprints, we formulate a binary integer program that globally balances sources of error to produce semantically parsed mass models with associated facade elements. We demonstrate our system on four city regions of varying complexity; our examples typically contain densely built urban blocks spanning hundreds of buildings. In our largest example, we produce a structured model of 37 city blocks spanning a total of 1, 011 buildings at a scale and quality previously impossible to achieve automatically

Positionnement visuel pour la réalité augmentée en environnement plan

Mesurer en temps réel la pose d'une caméra relativement à des repères tridimensionnels identifiés dans une image vidéo est un, sinon le pilier fondamental de la réalité augmentée. Nous proposons de résoudre ce problème dans des environnements bâtis, à l'aide de la visionpar ordinateur. Nous montrons qu'un système de positionnement plus précis que le GPS, et par ailleurs plus stable, plus rapide et moins coûteux en mémoire que d'autres systèmes de positionnement visuel introduits dans la littérature, peut êtreobtenu en faisant coopérer : approche probabiliste et géométrie aléatoire (détection a contrario des points de fuite del'image), apprentissage profond (proposition de boites contenant des façades, élaboration d'un descripteur de façades basé sur un réseau deneurones convolutifs), inférence bayésienne (recalage par espérance-maximisation d'un modèle géométrique et sémantique compactdes façades identifiées) et sélection de modèle (analyse des mouvements de la caméra par suivi de plans texturés). Nous décrivonsde plus une méthode de modélisation in situ, qui permet d'obtenir de manière fiable, de par leur confrontation immédiate à la réalité, des modèles 3D utiles au calcul de pose tel que nous l'envisageons

Scale aware modeling and monitoring of the urban energy chain

With energy modeling at different complexity levels for smart cities and the concurrent data availability revolution from connected devices, a steady surge in demand for spatial knowledge has been observed in the energy sector. This transformation occurs in population centers focused on efficient energy use and quality of life. Energy-related services play an essential role in this mix, as they facilitate or interact with all other city services. This trend is primarily driven by the current age of the Ger.: Energiewende or energy transition, a worldwide push towards renewable energy sources, increased energy use efficiency, and local energy production that requires precise estimates of local energy demand and production. This shift in the energy market occurs as the world becomes aware of human-induced climate change, to which the building stock has a significant contribution (40% in the European Union). At the current rate of refurbishment and building replacement, of the buildings existing in 2050 in the European Union, 75% would not be classified as energy-efficient. That means that substantial structural change in the built environment and the energy chain is required to achieve EU-wide goals concerning environmental and energy policy. These objectives provide strong motivation for this thesis work and are generally made possible by energy monitoring and modeling activities that estimate the urban energy needs and quantify the impact of refurbishment measures. To this end, a modeling library called aEneAs was developed in the scope of this thesis that can perform city-wide building energy modeling. The library performs its tasks at the level of a single building and was a first in its field, using standardized spatial energy data structures that allow for portability from one city to another. For data input, extensive use was made of digital twins provided from CAD, BIM, GIS, architectural models, and a plethora of energy data sources. The library first quantifies primary thermal energy demand and then the impact of refurbishment measures. Lastly, it estimates the potential of renewable energy production from solar radiation. aEneAs also includes network modeling components that consider energy distribution in the given context, showing a path toward data modeling and simulation required for distributed energy production at the neighborhood and district level. In order to validate modeling activities in solar radiation and green façade and roof installations, six spatial models were coupled with sensor installations. These digital twins are included in three experiments that highlight this monitoring side of the energy chain and portray energy-related use cases that utilize the spatially enabled web services SOS-SES-WNS, SensorThingsAPI, and FIWARE. To this author\u27s knowledge, this is the first work that surveys the capabilities of these three solutions in a unifying context, each having its specific design mindset. The modeling and monitoring activity and their corresponding literature review indicated gaps in scientific knowledge concerning data science in urban energy modeling. First, a lack of standardization regarding the spatial scales at which data is stored and used in urban energy modeling was observed. In order to identify the appropriate spatial levels for modeling and data aggregation, scale is explored in-depth in the given context and defined as a byproduct of resolution and extent, with ranges provided for both parameters. To that end, a survey of the encountered spatial scales and actors in six different geographical and cultural settings was performed. The information from this survey was used to put forth a standardized spatial scales definition and create a scale-dependent ontology for use in urban energy modeling. The ontology also provides spatially enabled persistent identifiers that resolve issues encountered with object relationships in modeling for inheritance, dependency, and association. The same survey also reveals two significant issues with data in urban energy modeling. These are data consistency across spatial scales and urban fabric contiguity. The impact of these issues and different solutions such as data generalization are explored in the thesis. Further advancement of scientific knowledge is provided specifically with spatial standards and spatial data infrastructure in urban energy modeling. A review of use cases in the urban energy chain and a taxonomy of the standards were carried out. These provide fundamental input for another piece of this thesis: inclusive software architecture methods that promote data integration and allow for external connectivity to modern and legacy systems. In order to reduce time-costly extraction, transformation, and load processes, databases and web services to ferry data to and from separate data sources were used. As a result, the spatial models become central linking elements of the different types of energy-related data in a novel perspective that differs from the traditional one, where spatial data tends to be non-interoperable / not linked with other data types. These distinct data fusion approaches provide flexibility in an energy chain environment with inconsistent data structures and software. Furthermore, the knowledge gathered from the experiments presented in this thesis is provided as a synopsis of good practices

Integrated modelling of control and adaptive building envelope: development of a modelling solution using a co-simulation approach

Adaptive building envelopes can dynamically adapt to environmental changes, often supported by a control system. Although adaptive building envelopes can play a significant role in improving thermal building performance, uncertainties and risks have led to a slow uptake in the built environment. A reason for this is the reluctance of practitioners to consider integrating adaptive building envelopes in building design. This may be due to Building Performance Simulation (BPS) tools that can be employed for performance prediction of design proposals with adaptive building envelopes. However, a shortcoming of existing tools is their limited adaptation that hinders proper modelling of the influence of control decisions on the dynamic behaviour of these building envelopes. This thesis investigates an approach for the integrated modelling of control and adaptive building envelope. To this aim, an interview-based industry study with experts in adaptive building envelope simulation was conducted. The interview study aimed to advance the understanding of the limitations of adaptive building envelope simulation in current design practice and to identify implications for future tool developments. The feedback from the interviewees was then used to inform the development of an integrated modelling approach using co-simulation, the accuracy and functionality of which were subsequently tested through a validation study and a multiple case study. The findings of the interview study outline the need for more flexible modelling approaches that enable designers to fully exploit adaptive building envelopes in building design. The proposed modelling approach for predicting the thermal performance of adaptive building envelopes has shown that its co-simulation setup seems to offer more flexibility in integrating the dynamic behaviour of adaptive building envelopes. What is now needed is to observe the execution of the modelling approach in design practice to obtain realistic feedback from its users and to verify that it works as intended

Le nuage de point intelligent

Discrete spatial datasets known as point clouds often lay the groundwork for decision-making applications. E.g., we can use such data as a reference for autonomous cars and robot’s navigation, as a layer for floor-plan’s creation and building’s construction, as a digital asset for environment modelling and incident prediction... Applications are numerous, and potentially increasing if we consider point clouds as digital reality assets. Yet, this expansion faces technical limitations mainly from the lack of semantic information within point ensembles. Connecting knowledge sources is still a very manual and time-consuming process suffering from error-prone human interpretation. This highlights a strong need for domain-related data analysis to create a coherent and structured information. The thesis clearly tries to solve automation problematics in point cloud processing to create intelligent environments, i.e. virtual copies that can be used/integrated in fully autonomous reasoning services. We tackle point cloud questions associated with knowledge extraction – particularly segmentation and classification – structuration, visualisation and interaction with cognitive decision systems. We propose to connect both point cloud properties and formalized knowledge to rapidly extract pertinent information using domain-centered graphs. The dissertation delivers the concept of a Smart Point Cloud (SPC) Infrastructure which serves as an interoperable and modular architecture for a unified processing. It permits an easy integration to existing workflows and a multi-domain specialization through device knowledge, analytic knowledge or domain knowledge. Concepts, algorithms, code and materials are given to replicate findings and extend current applications.Les ensembles discrets de données spatiales, appelés nuages de points, forment souvent le support principal pour des scénarios d’aide à la décision. Par exemple, nous pouvons utiliser ces données comme référence pour les voitures autonomes et la navigation des robots, comme couche pour la création de plans et la construction de bâtiments, comme actif numérique pour la modélisation de l'environnement et la prédiction d’incidents... Les applications sont nombreuses et potentiellement croissantes si l'on considère les nuages de points comme des actifs de réalité numérique. Cependant, cette expansion se heurte à des limites techniques dues principalement au manque d'information sémantique au sein des ensembles de points. La création de liens avec des sources de connaissances est encore un processus très manuel, chronophage et lié à une interprétation humaine sujette à l'erreur. Cela met en évidence la nécessité d'une analyse automatisée des données relatives au domaine étudié afin de créer une information cohérente et structurée. La thèse tente clairement de résoudre les problèmes d'automatisation dans le traitement des nuages de points pour créer des environnements intelligents, c'est-àdire des copies virtuelles qui peuvent être utilisées/intégrées dans des services de raisonnement totalement autonomes. Nous abordons plusieurs problématiques liées aux nuages de points et associées à l'extraction des connaissances - en particulier la segmentation et la classification - la structuration, la visualisation et l'interaction avec les systèmes cognitifs de décision. Nous proposons de relier à la fois les propriétés des nuages de points et les connaissances formalisées pour extraire rapidement les informations pertinentes à l'aide de graphes centrés sur le domaine. La dissertation propose le concept d'une infrastructure SPC (Smart Point Cloud) qui sert d'architecture interopérable et modulaire pour un traitement unifié. Elle permet une intégration facile aux flux de travail existants et une spécialisation multidomaine grâce aux connaissances liée aux capteurs, aux connaissances analytiques ou aux connaissances de domaine. Plusieurs concepts, algorithmes, codes et supports sont fournis pour reproduire les résultats et étendre les applications actuelles.Diskrete räumliche Datensätze, so genannte Punktwolken, bilden oft die Grundlage für Entscheidungsanwendungen. Beispielsweise können wir solche Daten als Referenz für autonome Autos und Roboternavigation, als Ebene für die Erstellung von Grundrissen und Gebäudekonstruktionen, als digitales Gut für die Umgebungsmodellierung und Ereignisprognose verwenden... Die Anwendungen sind zahlreich und nehmen potenziell zu, wenn wir Punktwolken als Digital Reality Assets betrachten. Allerdings stößt diese Erweiterung vor allem durch den Mangel an semantischen Informationen innerhalb von Punkt-Ensembles auf technische Grenzen. Die Verbindung von Wissensquellen ist immer noch ein sehr manueller und zeitaufwendiger Prozess, der unter fehleranfälliger menschlicher Interpretation leidet. Dies verdeutlicht den starken Bedarf an domänenbezogenen Datenanalysen, um eine kohärente und strukturierte Information zu schaffen. Die Arbeit versucht eindeutig, Automatisierungsprobleme in der Punktwolkenverarbeitung zu lösen, um intelligente Umgebungen zu schaffen, d.h. virtuelle Kopien, die in vollständig autonome Argumentationsdienste verwendet/integriert werden können. Wir befassen uns mit Punktwolkenfragen im Zusammenhang mit der Wissensextraktion - insbesondere Segmentierung und Klassifizierung - Strukturierung, Visualisierung und Interaktion mit kognitiven Entscheidungssystemen. Wir schlagen vor, sowohl Punktwolkeneigenschaften als auch formalisiertes Wissen zu verbinden, um schnell relevante Informationen mithilfe von domänenzentrierten Grafiken zu extrahieren. Die Dissertation liefert das Konzept einer Smart Point Cloud (SPC) Infrastruktur, die als interoperable und modulare Architektur für eine einheitliche Verarbeitung dient. Es ermöglicht eine einfache Integration in bestehende Workflows und eine multidimensionale Spezialisierung durch Gerätewissen, analytisches Wissen oder Domänenwissen. Konzepte, Algorithmen, Code und Materialien werden zur Verfügung gestellt, um Erkenntnisse zu replizieren und aktuelle Anwendungen zu erweitern

CAD-integrierte Isogeometrische Analyse und Entwurf leichter Tragwerke

Isogeometric methods are extended for the parametric design process of complex lightweight structures. Three novel methods for the coupling of different structural elements are proposed: rotational coupling, implicit geometry description, and frictionless sliding contact. Moreover, the necessary steps for the integration of the numerical analysis, including pre- and post-processing, in CAD are investigated. It is possible to base several different analyses on each other in order to parametrically represent a construction process with multiple steps.Die isogeometrischen Methoden werden zur Anwendung im parametrischen Entwurfsprozess von komplexen Leichtbaustrukturen erweitert. Hierzu werden drei neue Methoden zur Kopplung unterschiedlicher Strukturelemente vorgeschlagen: Rotationskopplung, implizite Geometriebeschreibung und reibungsfreier Gleitkontakt. Ferner werden die nötigen Schritte zur Einbindung von Pre- und Postprocessing für numerische Simulationen in CAD untersucht. Mehrere unterschiedliche Analysen können auf einander folgen und werden verlinkt, um den Aufbauprozess in mehreren Schritten vollparametrisch abzubilden

The flow of city life: An analysis of cinematography and urban form in New York and Los Angeles

This dissertation uses quantitative data on city cinematography and the morphological study of filming locations to identify how differences in ways of seeing cities, as shaped by cinematographic choices, are anchored both in differences in what is physically present as well as in differences in frameworks and expectations about what might be interesting or important to see. Four films are evaluated that are set in Los Angeles and New York, two cities recognized as paradigms in American urbanism: The Naked City (1948), The Long Goodbye (1970), Goodfellas (1990), and Pulp Fiction (1994). In general, the New York movies suggest the embeddedness of the individual in the city and its social life in ways tied closely to urban form, with the visual presentation of the street acting as an index to the position of the individual within the narrative. Los Angeles, by contrast, presents the city as a series of enclaves linked by infrastructure. The street as a sociologically relevant entity hardly exists, with the exception of a handful of chase scenes, as though only crisis can catalyze direct encounters with the streets of Los Angeles. Within individual movies, the depiction of city form reveals directorial idioms in the presentation of the narrative. The Naked City exploits corner shots to impart greater visual interest to the presentation of activity in the streets. The Long Goodbye shows the degradation of the distinction between public and private space as concurrent with a city form and culture that resists decoding. Goodfellas develops a grammar of views on the street that corresponds to the relationships of individual characters to overlapping social groups over time. Pulp Fiction mainly presents city locations as decontextualized to focus on dialogue and relationships, to sculpt urban form to meet the exigencies of the narrative, and to all the more powerfully introduce surprise. In the concluding chapter, the qualities of the city as presented in Goodfellas and Pulp Fiction and both of the cities are diagrammed and discussed relative to architectural precedents and ideas that might inform architectural design.Ph.D

Visualization, Adaptation, and Transformation of Procedural Grammars

Procedural shape grammars are powerful tools for the automatic generation of highly detailed 3D content from a set of descriptive rules. It is easy to encode variations in stochastic and parametric grammars, and an uncountable number of models can be generated quickly. While shape grammars offer these advantages over manual 3D modeling, they also suffer from certain drawbacks. We present three novel methods that address some of the limitations of shape grammars. First, it is often difficult to grasp the diversity of models defined by a given grammar. We propose a pipeline to automatically generate, cluster, and select a set of representative preview images for a grammar. The system is based on a new view attribute descriptor that measures how suitable an image is in representing a model and that enables the comparison of different models derived from the same grammar. Second, the default distribution of models in a stochastic grammar is often undesirable. We introduce a framework that allows users to design a new probability distribution for a grammar without editing the rules. Gaussian process regression interpolates user preferences from a set of scored models over an entire shape space. A symbol split operation enables the adaptation of the grammar to generate models according to the learned distribution. Third, it is hard to combine elements of two grammars to emerge new designs. We present design transformations and grammar co-derivation to create new designs from existing ones. Algorithms for fine-grained rule merging can generate a large space of design variations and can be used to create animated transformation sequences between different procedural designs. Our contributions to visualize, adapt, and transform grammars makes the procedural modeling methodology more accessible to non-programmers