Towards Realistic Pedestrian Route Planning

Pedestrian routing has its specific set of challenges, which are often neglected by state-of-the-art route planners. For instance, the lack of detailed sidewalk data and the inability to traverse plazas and parks in a natural way often leads to unappealing and suboptimal routes. In this work, we first propose to augment the network by generating sidewalks based on the street geometry and adding edges for routing over plazas and squares. Using this and further information, our query algorithm seamlessly handles node-to-node queries and queries whose origin or destination is an arbitrary location on a plaza or inside a park. Our experiments show that we are able to compute appealing pedestrian routes at negligible overhead over standard routing algorithms

Indoor And Outdoor Real Time Information Collection in Disaster Scenario

A disaster usually severely harms human health and property. After a disaster, great amount of information of a disaster area is needed urgently. The information not only indicates the severity of the disaster, but also is crucial for an efficient search and rescue process. In order to quickly and accurately collect real time information in a disaster scenario, a mobile platform is developed for an outdoor scenario and a localization and navigation system for responders is introduced for an indoor scenario. The mobile platform has been integrated to the DIORAMA system. It is built with a 6-wheel robot chassis along with an Arduino microcontroller. Controlled by a mounted Android smartphone, the mobile platform can receive commands from incident commanders and quickly respond to the commands. While patrolling in a disaster area, a constant RFID signal is collected to improve the localization accuracy of victims. Pictures and videos are also captured in order to enhance the situational awareness of rescuers. The design of the indoor information collection is focused on the responder side. During a disaster scenario, it is hard to track responders’ locations in an indoor environment. In this thesis, an indoor localization and navigation system based on Bluetooth low energy and Android is developed for helping responders report current location and quickly find the right path in the environment. Different localization algorithms are investigated and implemented. A navigation system based on A­* is also proposed

Efficient Object-Based Hierarchical Radiosity Methods

The efficient generation of photorealistic images is one of the main subjects in the field of computer graphics. In contrast to simple image generation which is directly supported by standard 3D graphics hardware, photorealistic image synthesis strongly adheres to the physics describing the flow of light in a given environment. By simulating the energy flow in a 3D scene global effects like shadows and inter-reflections can be rendered accurately. The hierarchical radiosity method is one way of computing the global illumination in a scene. Due to its limitation to purely diffuse surfaces solutions computed by this method are view independent and can be examined in real-time walkthroughs. Additionally, the physically based algorithm makes it well suited for lighting design and architectural visualization. The focus of this thesis is the application of object-oriented methods to the radiosity problem. By consequently keeping and using object information throughout all stages of the algorithms several contributions to the field of radiosity rendering could be made. By introducing a new meshing scheme, it is shown how curved objects can be treated efficiently by hierarchical radiosity algorithms. Using the same paradigm the radiosity computation can be distributed in a network of computers. A parallel implementation is presented that minimizes communication costs while obtaining an efficient speedup. Radiosity solutions for very large scenes became possible by the use of clustering algorithms. Groups of objects are combined to clusters to simulate the energy exchange on a higher abstraction level. It is shown how the clustering technique can be improved without loss in image quality by applying the same data-structure for both, the visibility computations and the efficient radiosity simulation.Eines der Schwerpunktthemen in der Computergraphik ist die effiziente Erzeugung von fotorealistischen Bildern. Im Gegensatz zur einfachen Bilderzeugung, die bereits durch gaengige 3D-Grafikhardware unterstuetzt wird, gehorcht die fotorealistische Bildsynthese physikalischen Gesetzen, die die Lichtausbreitung innerhalb einer bestimmten Umgebung beschreiben. Durch die Simulation der Energieausbreitung in einer dreidimensionalen Szene koennen globale Effekte wie Schatten und mehrfache Reflektionen wirklichkeitstreu dargestellt werden. Die hierarchische Radiositymethode (Hierarchical Radiosity) ist eine Moeglichkeit, um die globale Beleuchtung innerhalb einer Szene zu berechnen. Da diese Methode auf die Verwendung von rein diffus reflektierenden Oberflaechen beschraenkt ist, sind damit errechnete Loesungen blickwinkelunabhaengig und lassen sich in Echtzeit am Bildschirm durchwandern. Zudem ist dieser Algorithmus aufgrund der verwendeten physikalischen Grundlagen sehr gut zur Beleuchtungssimulation und Architekturvisualisierung geeignet. Den Schwerpunkt dieser Doktorarbeit stellt die Anwendung objektbasierter Methoden auf das Radiosityproblem dar. Durch konsequente Ausnutzung von Objektinformationen waehrend aller Berechnungsschritte konnten verschiedene Verbesserungen im Rahmen der hierarchischen Radiositymethode erzielt werden. Gekruemmte Objekte koennen aufgrund eines neuen Flaechenunterteilungsverfahrens nun effizient durch den hierarchischen Radiosityalgorithmus dargestellt werden. Dieses Verfahren ermoeglicht ebenso eine effiziente Parallelisierung des hierarchischen Radiosityalgorithmus. Es wird ein parallele Implementierung vorgestellt, die unter Minimierung der Kommunikationskosten eine effiziente Geschwindigkeitssteigerung erzielt. Radiosityberechnungen fuer sehr grosse Szenen sind nur durch Verwendung sogenannter Clustering-Algorithmen moeglich. Dabei werden Gruppen von Objekten zu Clustern kombiniert um den Energieaustausch zwischen Oberflaechen stellvertretend auf einem hoeheren Abstraktionsniveau durchzufuehren. Durch Verwendung derselben Datenstruktur fuer Sichtbarkeitsberechnungen und fuer die Steuerung der Radiositysimulation wird gezeigt, wie das Clusteringverfahren ohne Qualitaetsverluste verbessert werden kann

Reasoning with Mixed Qualitative-Quantitative Representations of Spatial Knowledge

Drastic transformations in human settlements are caused by extreme events. As a consequence, descriptions of an environment struck by an extreme event, based on spatial data collected before the event, become suddenly unreliable. On the other hand, time critical actions taken for responding to extreme events require up-to-date spatial information. Traditional methods for spatial data collection are not able to provide updated information rapidly enough, calling for the development of new data collection methods. Reports provided by actors involved in the response operations can be considered as an alternative source of spatial information. Indeed, reports often convey spatial descriptions of the environment. The extraction of spatial descriptions from such reports can serve a fundamental role to update existing information which is usually maintained within, and by means of, Geographic Information Systems. However, spatial information conveyed by human reports has qualitative characteristics, that strongly differ from the quantitative nature of spatial information stored in Geographic Information Systems. Methodologies for integrating qualitative and quantitative spatial information are required in order to exploit human reports for updating existing descriptions of spatial knowledge. Although a significant amount of research has been carried on how to represent and reason on qualitative data and qualitative information, relatively little work exists on developing techniques to combine the different methodologies. The work presented in this thesis extends previous works by introducing a hybrid reasoning system--able to deal with mixed qualitative-quantitative representations of spatial knowledge--combining techniques developed separately for qualitative spatial reasoning and quantitative data analysis. The system produces descriptions of the spatial extent of those entities that have been modified by the event (such as collapsed buildings), or that were not existing before the event (such as fire or ash clouds). Furthermore, qualitative descriptions are produced for all entities in the environment. The former descriptions allow for overlaying on a map the information interpreted from human reports, while the latter triggers warning messages to people involved in decision making operations. Three main system functionalities are investigated in this work: The first allows for translating qualitative information into quantitative descriptions. The second aims at translating quantitative information into qualitative relations. Finally, the third allows for performing inference operations with information given partly qualitatively and partly quantitatively for boosting the spatial knowledge the system is able to produce

Open3D: Crowd-Sourced Distributed Curation of City Models

Detailed, large-scale 3D models of cities are important assets for many applications. While creating such models is difficult and time consuming, keeping them updated is even more challenging. In comparison, in many domains, crowd-sourcing of data is now an established process for expanding the scope or detail of data sets. In this paper, we describe the initial prototype implementation of Open3D, a crowd-sourcing platform for distributed curation of large-scale city models. We present an open architecture with interfaces that clearly separate model storage and indexing from viewing or editing. To support collaborative editing of extremely large models, we propose to use a modeling and model description paradigm that can integrate polygon-based modeling with parametric operations. We demonstrate the main concepts and prototype through an online city model that can be synchronously edited by multiple users, with live changes being propagated among clients. The main implementation consists of a set of web services, which support key functions such as model storage, locks for editing and spatial queries; a light-weight viewer based on the Cesium library, which runs on desktops and mobile devices; and a prototype editor, which clients can install to edit the models