Automated Pattern Detection and Generalization of Building Groups

This dissertation focuses on the topic of building group generalization by considering the detection of building patterns. Generalization is an important research field in cartography, which is part of map production and the basis for the derivation of multiple representation. As one of the most important features on map, buildings occupy large amount of map space and normally have complex shape and spatial distribution, which leads to that the generalization of buildings has long been an important and challenging task. For social, architectural and geographical reasons, the buildings were built with some special rules which forms different building patterns. Building patterns are crucial structures which should be carefully considered during graphical representation and generalization. Although people can effortlessly perceive these patterns, however, building patterns are not explicitly described in building datasets. Therefore, to better support the subsequent generalization process, it is important to automatically recognize building patterns. The objective of this dissertation is to develop effective methods to detect building patterns from building groups. Based on the identified patterns, some generalization methods are proposed to fulfill the task of building generalization. The main contribution of the dissertation is described as the following five aspects: (1) The terminology and concept of building pattern has been clearly explained; a detailed and relative complete typology of building patterns has been proposed by summarizing the previous researches as well as extending by the author; (2) A stroke-mesh based method has been developed to group buildings and detect different patterns from the building groups; (3) Through the analogy between line simplification and linear building group typification, a stroke simplification based typification method has been developed aiming at solving the generalization of building groups with linear patterns; (4) A mesh-based typification method has been developed for the generalization of the building groups with grid patterns; (5) A method of extracting hierarchical skeleton structures from discrete buildings have been proposed. The extracted hierarchical skeleton structures are regarded as the representations of the global shape of the entire region, which is used to control the generalization process. With the above methods, the building patterns are detected from the building groups and the generalization of building groups are executed based on the patterns. In addition, the thesis has also discussed the drawbacks of the methods and gave the potential solutions.:Abstract I Kurzfassung III Contents V List of Figures IX List of Tables XIII List of Abbreviations XIV Chapter 1 Introduction 1 1.1 Background and motivation 1 1.1.1 Cartographic generalization 1 1.1.2 Urban building and building patterns 1 1.1.3 Building generalization 3 1.1.4 Hierarchical property in geographical objects 3 1.2 Research objectives 4 1.3 Study area 5 1.4 Thesis structure 6 Chapter 2 State of the Art 8 2.1 Operators for building generalization 8 2.1.1 Selection 9 2.1.2 Aggregation 9 2.1.3 Simplification 10 2.1.4 Displacement 10 2.2 Researches of building grouping and pattern detection 11 2.2.1 Building grouping 11 2.2.2 Pattern detection 12 2.2.3 Problem analysis . 14 2.3 Researches of building typification 14 2.3.1 Global typification 15 2.3.2 Local typification 15 2.3.3 Comparison analysis 16 2.3.4 Problem analysis 17 2.4 Summary 17 Chapter 3 Using stroke and mesh to recognize building group patterns 18 3.1 Abstract 19 3.2 Introduction 19 3.3 Literature review 20 3.4 Building pattern typology and study area 22 3.4.1 Building pattern typology 22 3.4.2 Study area 24 3.5 Methodology 25 3.5.1 Generating and refining proximity graph 25 3.5.2 Generating stroke and mesh 29 3.5.3 Building pattern recognition 31 3.6 Experiments 33 3.6.1 Data derivation and test framework 33 3.6.2 Pattern recognition results 35 3.6.3 Evaluation 39 3.7 Discussion 40 3.7.1 Adaptation of parameters 40 3.7.2 Ambiguity of building patterns 44 3.7.3 Advantage and Limitation 45 3.8 Conclusion 46 Chapter 4 A typification method for linear building groups based on stroke simplification 47 4.1 Abstract 48 4.2 Introduction 48 4.3 Detection of linear building groups 50 4.3.1 Stroke-based detection method 50 4.3.2 Distinguishing collinear and curvilinear patterns 53 4.4 Typification method 55 4.4.1 Analogy of building typification and line simplification 55 4.4.2 Stroke generation 56 4.4.3 Stroke simplification 57 4.5 Representation of newly typified buildings 60 4.6 Experiment 63 4.6.1 Linear building group detection 63 4.6.2 Typification results 65 4.7 Discussion 66 4.7.1 Comparison of reallocating remained nodes 66 4.7.2 Comparison with classic line simplification method 67 4.7.3 Advantage 69 4.7.4 Further improvement 71 4.8 Conclusion 71 Chapter 5 A mesh-based typification method for building groups with grid patterns 73 5.1 Abstract 74 5.2 Introduction 74 5.3 Related work 75 5.4 Methodology of mesh-based typification 78 5.4.1 Grid pattern classification 78 5.4.2 Mesh generation 79 5.4.3 Triangular mesh elimination 80 5.4.4 Number and positioning of typified buildings 82 5.4.5 Representation of typified buildings 83 5.4.6 Resizing Newly Typified Buildings 85 5.5 Experiments 86 5.5.1 Data derivation 86 5.5.2 Typification results and evaluation 87 5.5.3 Comparison with official map 91 5.6 Discussion 92 5.6.1 Advantages 92 5.6.2 Further improvements 93 5.7 Conclusion 94 Chapter 6 Hierarchical extraction of skeleton structures from discrete buildings 95 6.1 Abstract 96 6.2 Introduction 96 6.3 Related work 97 6.4 Study area 99 6.5 Hierarchical extraction of skeleton structures 100 6.5.1 Proximity Graph Network (PGN) of buildings 100 6.5.2 Centrality analysis of proximity graph network 103 6.5.3 Hierarchical skeleton structures of buildings 108 6.6 Generalization application 111 6.7 Experiment and discussion 114 6.7.1 Data statement 114 6.7.2 Experimental results 115 6.7.3 Discussion 118 6.8 Conclusions 120 Chapter 7 Discussion 121 7.1 Revisiting the research problems 121 7.2 Evaluation of the presented methodology 123 7.2.1 Strengths 123 7.2.2 Limitations 125 Chapter 8 Conclusions 127 8.1 Main contributions 127 8.2 Outlook 128 8.3 Final thoughts 131 Bibliography 132 Acknowledgements 142 Publications 14

Automated processing for map generalization using web services

In map generalization various operators are applied to the features of a map in order to maintain and improve the legibility of the map after the scale has been changed. These operators must be applied in the proper sequence and the quality of the results must be continuously evaluated. Cartographic constraints can be used to define the conditions that have to be met in order to make a map legible and compliant to the user needs. The combinatorial optimization approaches shown in this paper use cartographic constraints to control and restrict the selection and application of a variety of different independent generalization operators into an optimal sequence. Different optimization techniques including hill climbing, simulated annealing and genetic deep search are presented and evaluated experimentally by the example of the generalization of buildings in blocks. All algorithms used in this paper have been implemented in a web services framework. This allows the use of distributed and parallel processing in order to speed up the search for optimized generalization operator sequence

Generalization of tiled models with curved surfaces using typification

Especially for landmark buildings or in the context of cultural heritage documentation, highly detailed digital models are being created in many places. In some of these models, surfaces are represented by tiles which are individually modeled as solid shapes. In many applications, the high complexity of these models has to be reduced for more x efficient visualization and analysis. In our paper, we introduce an approach to derive versions at different scales from such a model through the generalization method of typification that works for curved underlying surfaces. Using the example of tiles placed on a curved roof - which occur, for example, very frequently in ancient Chinese architecture, the original set of tiles is replaced by fewer but bigger tiles while keeping a similar appearance. In the first step, the distribution of the central points of the tiles is approximated by a spline surface. This is necessary because curved roof surfaces cannot be approximated by planes at large scales. After that, the new set of tiles with less rows and/or columns is distributed along a spline surface generated from a morphing of the original surface towards a plane. The degree of morphing is dependent on the desired target scale. If the surface can be represented as a plane at the given resolution, the tiles may be converted to a bump map or a simple texture for visualization. In the final part, a perception-based method using CSF (contrast sensitivity function) is introduced to determine an appropriate LoD (level of detail) version of the model for a given viewing scenario (point of view and camera properties) at runtime.BMBF/GDI-Grid projectNational Basic Reseach Program of China/2010CB731800National High Technology Research and Development Program of China/2008AA12160

Designing Multi-Scale Maps: Lessons Learned from Existing Practices

International audienceMapping applications display multi-scale maps where zooming in and out triggers the display of different maps at different scales. Multi-scale maps strongly augmented the potential uses of maps, compared to the traditional single-scaled paper maps. But the exploration of the multi-scale maps can be cognitively difficult for users because the content of the maps can be very different at different scales. This paper seeks to identify the factors in the design of map content and style that increase or decrease the exploration cognitive load, in order to improve multi-scales map design. We studied sixteen existing examples of multi-scale maps to identify these factors that influence a fluid zooming interaction. Several different analyses were conducted on these sixteen multiscale maps. We first conducted a guided visual exploration of the maps, and a detailed study of the scales of the maps, to identify general trends of good practices (e.g. the WMTS standard that defines zoom levels is widely used) and potential ways of improvement (e.g. a same map is often used at multiple successive zoom levels). Then, we focused on the visual complexity of the multi-scale maps by analyzing how it varies, continuously or not, across scales, using clutter measures, which showed a peak of complexity at zoom level 12 of the WMTS standard. Finally, we studied how buildings and roads are subject to abstraction changes across scales (e.g. at what zoom level individual buildings turn into built-up areas), which can be one of the causes of exploration difficulties. We identified some good practices to reduce the impact of abstraction changes, for instance by mixing different levels of abstraction in the same map.Les applications cartographiques actuelles affichent des cartes multi-échelles, dans lesquelles une interaction de zoom avant ou arrière déclenche l'affichage d'une nouvelle carte à plus grande ou plus petite échelle. Ces cartes multi-échelles permettent des utilisations beaucoup plus vastes et diverses que les traditionnelles cartes topographiques imprimées sur papier. Mais l'exploration interactive de ces cartes peut entrainer une charge cognitive assez lourde car le contenu des cartes peut varier très fortement entre les différentes échelles, et il devient difficile de se repérer. Cet article cherche à identifier les facteurs du design cartographique qui influent sur cette charge cognitive lors d'un changement d'échelle, avec pour objectif à long terme d'améliorer les pratiques de conception de cartes multi-échelles. Nous avons ainsi étudié seize exemples de cartes multi-échelles pour identifier les facteurs permettant d'influer sur la fluidité du zoom. Plusieurs analyses différentes ont été menées sur ces seize cartes. Nous avons d'abord réalisé une analyse visuelle de ces cartes selon divers critères, et une étude détaillée des différentes échelles utilisées, afin d'identifier des tendances (comme l'utilisation massive du standard WMTS), ou des pistes d'amélioration (par exemple, l'utilisation d'une même carte à plusieurs échelles parait sous-optimale). Nous avons ensuite mesuré la variation de complexité visuelle des cartes quand les échelles varient à l'aide de mesures de l'effet de ≪ clutter ≫ ce qui a notamment montré un pic de complexité pour les cartes présentées au niveau de zoom n∘12 du standard WMTS. Enfin, nous avons étudié les changements de niveau d'abstraction spécifiquement sur les thèmes ≪ bâti ≫ et ≪ routes ≫ (par exemple à quelle échelle la représentation des bâtiments individuels est remplacée par une représentation de l'aire urbaine), ce qui a permis de mettre en valeur une cause possible de ces difficultés d'exploration. Des bonnes pratiques ont été identifiées pour une meilleure transition entre les niveaux d'abstraction, notamment en les combinant dans une même carte à une échelle de transition

Progressive Block Graying and Landmarks Enhancing as Intermediate Representations between Buildings and Urban Areas

workshopInternational audienceGeovisualization applications that allow the navigation between maps at different scales while zooming in and out often provide no smooth transition between the individual building level of abstraction and the representation of whole urban areas as polygons. In order to reduce the cognitive load of the user, we seek to add intermediate zoom levels with intermediate and progressive abstractions between buildings and urban areas. This paper proposes a method based on progressive block graying while enhancing building landmarks, to derive these intermediate representations from the individual buildings. Block graying is based on an automatic building classification, and a multiple criteria decision technique to infer inner city blocks. The landmarks identification relies on machine learning and several criteria based on geometry and spatial relations. The method is tested with real cartographic data between the 1:25k (with individual buildings) and the 1:100k scale (with urban areas): transitions with one, two, or three intermediate representations are derived and tested

Inferring High-level Geographical Concepts via Knowledge Graph and Multi-scale Data Integration: A Case Study of C-shaped Building Pattern Recognition

Effective building pattern recognition is critical for understanding urban form, automating map generalization, and visualizing 3D city models. Most existing studies use object-independent methods based on visual perception rules and proximity graph models to extract patterns. However, because human vision is a part-based system, pattern recognition may require decomposing shapes into parts or grouping them into clusters. Existing methods may not recognize all visually aware patterns, and the proximity graph model can be inefficient. To improve efficiency and effectiveness, we integrate multi-scale data using a knowledge graph, focusing on the recognition of C-shaped building patterns. First, we use a property graph to represent the relationships between buildings within and across different scales involved in C-shaped building pattern recognition. Next, we store this knowledge graph in a graph database and convert the rules for C-shaped pattern recognition and enrichment into query conditions. Finally, we recognize and enrich C-shaped building patterns using rule-based reasoning in the built knowledge graph. We verify the effectiveness of our method using multi-scale data with three levels of detail (LODs) collected from the Gaode Map. Our results show that our method achieves a higher recall rate of 26.4% for LOD1, 20.0% for LOD2, and 9.1% for LOD3 compared to existing approaches. We also achieve recognition efficiency improvements of 0.91, 1.37, and 9.35 times, respectively

CartAGen: an Open Source Research Platform for Map Generalization

International audienceAutomatic map generalization is a complex task that is still a research problem and requires the development of research prototypes before being usable in productive map processes. In the meantime, reproducible research principles are becoming a standard. Publishing reproducible research means that researchers share their code and their data so that other researchers might be able to reproduce the published experiments, in order to check them, extend them, or compare them to their own experiments. Open source software is a key tool to share code and software, and CartAGen is the first open source research platform that tackles the overall map generalization problem: not only the building blocks that are generalization algorithms, but also methods to chain them, and spatial analysis tools necessary for data enrichment. This paper presents the CartAGen platform, its architecture and its components. The main component of the platform is the implementation of several multi-agent based models of the literature such as AGENT, CartACom, GAEL, CollaGen, or DIOGEN. The paper also explains and discusses different ways, as a researcher, to use or to contribute to CartAGen

Bicriteria Aggregation of Polygons via Graph Cuts

We present a new method for the task of detecting groups of polygons in a given geographic data set and computing a representative polygon for each group. This task is relevant in map generalization where the aim is to derive a less detailed map from a given map. Following a classical approach, we define the output polygons by merging the input polygons with a set of triangles that we select from a constrained Delaunay triangulation of the input polygons\u27 exterior. The innovation of our method is to compute the selection of triangles by solving a bicriteria optimization problem. While on the one hand we aim at minimizing the total area of the outputs polygons, we aim on the other hand at minimizing their total perimeter. We combine these two objectives in a weighted sum and study two computational problems that naturally arise. In the first problem, the parameter that balances the two objectives is fixed and the aim is to compute a single optimal solution. In the second problem, the aim is to compute a set containing an optimal solution for every possible value of the parameter. We present efficient algorithms for these problems based on computing a minimum cut in an appropriately defined graph. Moreover, we show how the result set of the second problem can be approximated with few solutions. In an experimental evaluation, we finally show that the method is able to derive settlement areas from building footprints that are similar to reference solutions

A heterogeneous data-based proposal for procedural 3D cities visualization and generalization

Ce projet de thèse est né d'un projet de collaboration entre l'équipe de recherche VORTEX/ Objets visuels: de la réalité à l'expression (maintenant REVA: Réel Expression Vie Artificielle) à l'IRIT : Institut de Recherche en Informatique de Toulouse d'une part et de professionnels de l'éducation, entreprises et entités publiques d'autre part. Le projet de collaboration SCOLA est essentiellement une plate-forme d'apprentissage en ligne basée sur l'utilisation des jeux sérieux dans les écoles. Il aide les utilisateurs à acquérir et à repérer des compétences prédéfinies. Cette plate-forme offre aux enseignants un nouvel outil flexible qui crée des scénarios liés à la pédagogie et personnalise les dossiers des élèves. Plusieurs contributions ont été attribuées à l'IRIT. L'une d'elles consiste à suggérer une solution pour la création automatique d'environnements 3D, à intégrer au scénario du jeu. Cette solution vise à empêcher les infographistes 3D de modéliser manuellement des environnements 3D détaillés et volumineux, ce qui peut être très coûteux et prendre beaucoup de temps. Diverses applications et prototypes ont été développés pour permettre à l'utilisateur de généraliser et de visualiser son propre monde virtuel principalement à partir d'un ensemble de règles. Par conséquent, il n'existe pas de schéma de représentation unique dans le monde virtuel en raison de l'hétérogénéité et de la diversité de la conception de contenus 3D, en particulier des modèles de ville. Cette contrainte nous a amené à nous appuyer largement dans notre projet sur de vraies données urbaines 3D au lieu de données personnalisées prédéfinies par le concepteur de jeu. Les progrès réalisés en infographie, les capacités de calcul élevées et les technologies Web ont largement révolutionné les techniques de reconstruction et de visualisation des données. Ces techniques sont appliquées dans divers domaines, en commençant par les jeux vidéo, les simulations et en terminant par les films qui utilisent des espaces générés de manière procédurale et des animations de personnages. Bien que les jeux informatiques modernes n'aient pas les mêmes restrictions matérielles et de mémoire que les anciens jeux, la génération procédurale est fréquemment utilisée pour créer des jeux, des cartes, des niveaux, des personnages ou d'autres facettes aléatoires uniques sur chaque jeu. Actuellement, la tendance est déplacée vers les SIG: Systèmes d'Information Géographiques pour créer des mondes urbains, en particulier après leur mise en œuvre réussie dans le monde entier afin de prendre en charge de nombreuses domaines d'applications. Les SIG sont plus particulièrement dédiés à des applications telles que la simulation, la gestion des catastrophes et la planification urbaine, avec une grande utilisation plus ou moins limitée dans les jeux, par exemple le jeu "Minecraft", dont la dernière version propose une cartographie utilisant des villes du monde réel Geodata in Minecraft. L'utilisation des données urbaines existantes devient de plus en plus répandue dans les applications cartographiques pour deux raisons principales: premièrement, elle permet de comprendre le contenu spatial d'objets urbains de manière plus logique et, deuxièmement, elle fournit une plate-forme commune pour intégrer des informations au niveau de la ville provenant de différents environnements ou ressources et les rendre accessibles aux utilisateurs. Un modèle de ville virtuelle en 3D est une représentation numérique de l'espace urbain qui décrit les propriétés géométriques, topologiques, sémantiques et d'apparence de ses composants. En général, un MV3D\footnote{Modèle de Ville en 3D} sert de plate-forme d'intégration pour plusieurs facettes d'un espace d'informations urbain, comme l'a souligné "Batty": "En bref, les nouveaux modèles ne sont pas simplement la géométrie numérique des modèles traditionnels, mais des bases de données à grande échelle pouvant être visualisées en 3D. En tant que tels, ils représentent déjà un moyen de fusionner des données symboliques ou thématiques plus abstraites, même des modèles symboliques, dans ce mode de représentation".This thesis project was born from a collaborative project between the research team VORTEX / Visual objects: from reality to expression (now REVA: Real Expression Artificial Life) at IRIT: Institute of Research in Computer Science Toulouse on the one hand and education professionals, companies and public entities on the other.The SCOLA collaborative project is essentially an online learning platform based on the use of serious games in schools. It helps users to acquire and track predefined skills. This platform provides teachers with a new flexible tool that creates pedagogical scenarios and personalizes student records. Several contributions have been attributed to IRIT. One of these is to suggest a solution for the automatic creation of 3D environments, to integrate into the game scenario. This solution aims to prevent 3D graphic designers from manually modeling detailed and large 3D environments, which can be very expensive and take a lot of time. Various applications and prototypes have been developed to allow the user to generalize and visualize their own virtual world primarily from a set of rules. Therefore, there is no single representation scheme in the virtual world due to the heterogeneity and diversity of 3D content design, especially city models. This constraint has led us to rely heavily on our project on real 3D urban data instead of custom data predefined by the game designer. Advances in computer graphics, high computing capabilities, and Web technologies have revolutionized data reconstruction and visualization techniques. These techniques are applied in a variety of areas, starting with video games, simulations, and ending with movies that use procedurally generated spaces and character animations. Although modern computer games do not have the same hardware and memory restrictions as older games, procedural generation is frequently used to create unique games, cards, levels, characters, or other random facets on each. Currently, the trend is shifting towards GIS : Geographical Information Systems to create urban worlds, especially after their successful implementation around the world to support many areas of applications. GIS are more specifically dedicated to applications such as simulation, disaster management and urban planning, with a great use more or less limited in games, for example the game "Minecraft", the latest version offers a map using real world cities Geodata in Minecraft. The use of existing urban data is becoming more and more widespread in cartographic applications for two main reasons: first, it makes it possible to understand the spatial content of urban objects in a more logical way and, secondly, it provides a common platform to integrate city-level information from different environments or resources and make them available to users. A 3D virtual city model is a digital representation of urban space that describes the geometric, topological, semantic, and appearance properties of its components. In general, an MV3D: 3D City Model serves as an integration platform for many facets of an urban information space, as "Batty" pointed out: "In short, the new models are not just the digital geometry of traditional models, but large-scale databases that can be visualized in 3D. As such, they already represent a way to merge more abstract symbolic or thematic data, even symbolic patterns, into this mode of representation"