Space colonisation based procedural road generation

Dissertação de mestrado em Computer ScienceProcedural generation of content has been studied for quite some time and it is increasingly relevant in scientific areas and in video-game and film industries. Procedural road layout generation has been traditionally approached using L-Systems, with some works exploring alternative avenues. Although originally conceived for biological systems modelling, the adequacy of L-Systems as a base for road generation has been demonstrated in several works. In this context, this work presents an alternative approach for procedural road layout generation that is also inspired by plant generation algorithms: space colonisation. In particular, this work uses the concept of attraction points introduced in space colonisation as its base to produce road layouts, both in urban and inter-city environments. As will be shown, the usage of attraction points provides an intuitive way to parameterise a road layout. The original Space Colonization Algorithm (SCA) generates a tree like structure, but in this work, the extensions made aim to fully generate a inter-connected road network. As most previous methods the method has two phases. A first phase generates what is mostly a tree structure growing from user defined road segments. The second phase performs the inter connectivity among the roads created in the first phase. The original SCA parameters such as the killradius help to control the capillarity of the road layout, the number of attraction points used by each segment will dictate its relevance establishing a road hierarchy naturally dependent on the distribution of the attraction points on the terrain. An angle control allows the creation of grid like or more organic road layouts. The distribution of the attraction points in the terrain can be conditioned by boundary maps, containing parks, sea, rivers, and other forbidden areas. Population density maps can be used to supply an explicit probabilistic distribution to the attraction points. Flow-fields can be used to dictate the flow of the road layout. Elevation maps provide an additional restriction regarding the steepness of the roads. The tests were executed within a graphic toolbox developed simultaneously. The results are exported to a geographical information file format, GeoJSON, and then maps are rendered using a geospatial visualisation and processing framework called Mapnik. For the most part, parameter settings were intuitively reflected on the road layout and this method can be seen as a first step towards fully exploring the usage of attraction points in the context of road layout.Gradualmente a geração procedimental de conteúdo tem-se tornado cada vez mais relevante, sendo maioritariamente aplicada em industrias como a dos vídeo-jogos e cinema. No que toca à geração procedimental de redes de estradas, grande parte das abordagens em torno deste tema são baseadas em L-Systems. Embora a área de aplicação dos L-Systems tenha sido originalmente para produzir modelos de sistemas biológicos, mostrou também ser um algoritmo adequado para a geração procedimental de redes de estradas. Este trabalho apresenta uma abordagem alternativa à geração procedimental de redes de estradas que também é inspirada num algoritmo procedimental de geração de plantas, colonização espacial, utilizando o conceito de pontos de atracão como base para gerar padrões de estradas. Como será demonstrado, a utilização de pontos de atracão fornece uma maneira intuitiva de parametrizar um padrão de estradas desejado. Como a maioria dos trabalhos feitos nesta área, este método tem duas fases. A primeira fase gera uma rede semelhante a uma árvore criada a partir de um ou mais segmentos iniciais da rede determinados pelo utilizador. A segunda fase trata de interligar as estradas geradas na primeira fase. Os parâmetros iniciais do algoritmo de colonização espacial, como o kill radius, ajudam a controlar a capilaridade da rede, os pontos de atracão que influenciam cada segmento irão ditar a sua relevância na rede geral, estabelecendo a noção de hierarquia de estradas, dependendo da distribuição de pontos de atracão no terreno. O controlo do ângulo entre segmentos permite a criação de padrões de estradas tanto em forma de grelha como padrões mais orgânicos. A distribuição dos pontos de atracão no terreno pode ser influenciada por mapas de fronteira, que contem as áreas válidas e/ou inválidas, como parques, mar, rios, e outras áreas proibidas. Mapas de densidade populacional podem ser usados para fornecer uma distribuição probabilística dos pontos de atracão. Campos de forças, podem ser usados para ditar o fluxo da rede de estradas. Mapas de elevação oferecem uma restrição adicional tendo em conta a inclinação das estradas. De um modo geral, as definições de parâmetros refletiram-se de um modo intuitivo nos padrões de redes de estradas gerados, e este trabalho pode ser considerado como um primeiro passo na exploração do conceito de pontos de atracão na área da geração de redes de estradas

Quantifiable isovist and graph-based measures for automatic evaluation of different area types in virtual terrain generation

© 2013 IEEE. This article describes a set of proposed measures for characterizing areas within a virtual terrain in terms of their attributes and their relationships with other areas for incorporating game designers\u27 intent in gameplay requirement-based terrain generation. Examples of such gameplay elements include vantage point, strongholds, chokepoints and hidden areas. Our measures are constructed on characteristics of an isovist, that is, the volume of visible space at a local area and the connectivity of areas within the terrain. The calculation of these measures is detailed, in particular we introduce two new ways to accurately and efficiently calculate the 3D isovist volume. Unlike previous research that has mainly focused on aesthetic-based terrain generation, the proposed measures address a gap in gameplay requirement-based terrain generation-the need for a flexible mechanism to automatically parameterise specified areas and their associated relationships, capturing semantic knowledge relating to high level user intent associated with specific gameplay elements within the virtual terrain. We demonstrate applications of using the measures in an evolutionary process to automatically generate terrains that include specific gameplay elements as defined by a game designer. This is significant as this shows that the measures can characterize different gameplay elements and allow gameplay elements consistent with the designers\u27 intents to be generated and positioned in a virtual terrain without the need to specify low-level details at a model or logic level, hence leading to higher productivity and lower cost

Quantifiable isovist and graph-based measures for automatic evaluation of different area types in virtual terrain generation

© 2013 IEEE. This article describes a set of proposed measures for characterizing areas within a virtual terrain in terms of their attributes and their relationships with other areas for incorporating game designers\u27 intent in gameplay requirement-based terrain generation. Examples of such gameplay elements include vantage point, strongholds, chokepoints and hidden areas. Our measures are constructed on characteristics of an isovist, that is, the volume of visible space at a local area and the connectivity of areas within the terrain. The calculation of these measures is detailed, in particular we introduce two new ways to accurately and efficiently calculate the 3D isovist volume. Unlike previous research that has mainly focused on aesthetic-based terrain generation, the proposed measures address a gap in gameplay requirement-based terrain generation-the need for a flexible mechanism to automatically parameterise specified areas and their associated relationships, capturing semantic knowledge relating to high level user intent associated with specific gameplay elements within the virtual terrain. We demonstrate applications of using the measures in an evolutionary process to automatically generate terrains that include specific gameplay elements as defined by a game designer. This is significant as this shows that the measures can characterize different gameplay elements and allow gameplay elements consistent with the designers\u27 intents to be generated and positioned in a virtual terrain without the need to specify low-level details at a model or logic level, hence leading to higher productivity and lower cost

Example-Based Urban Modeling

The manual modeling of virtual cities or suburban regions is an extremely time-consuming task, which expects expert knowledge of different fields. Existing modeling tool-sets have a steep learning curve and may need special education skills to work with them productively. Existing automatic methods rely on rule sets and grammars to generate urban structures; however, their expressiveness is limited by the rule-sets. Expert skills are necessary to typeset rule sets successfully and, in many cases, new rule-sets need to be defined for every new building style or street network style. To enable non-expert users, the possibility to construct urban structures for individual experiments, this work proposes a portfolio of novel example-based synthesis algorithms and applications for the controlled generation of virtual urban environments. The notion example-based denotes here that new virtual urban environments are created by computer programs that re-use existing digitized real-world data serving as templates. The data, i.e., street networks, topography, layouts of building footprints, or even 3D building models, necessary to realize the envisioned task is already publicly available via online services. To enable the reuse of existing urban datasets, novel algorithms need to be developed by encapsulating expert knowledge and thus allow the controlled generation of virtual urban structures from sparse user input. The focus of this work is the automatic generation of three fundamental structures that are common in urban environments: road networks, city block, and individual buildings. In order to achieve this goal, the thesis proposes a portfolio of algorithms that are briefly summarized next. In a theoretical chapter, we propose a general optimization technique that allows formulating example-based synthesis as a general resource-constrained k-shortest path (RCKSP) problem. From an abstract problem specification and a database of exemplars carrying resource attributes, we construct an intermediate graph and employ a path-search optimization technique. This allows determining either the best or the k-best solutions. The resulting algorithm has a reduced complexity for the single constraint case when compared to other graph search-based techniques. For the generation of road networks, two different techniques are proposed. The first algorithm synthesizes a novel road network from user input, i.e., a desired arterial street skeleton, topography map, and a collection of hierarchical fragments extracted from real-world road networks. The algorithm recursively constructs a novel road network reusing these fragments. Candidate fragments are inserted into the current state of the road network, while shape differences will be compensated by warping. The second algorithm synthesizes road networks using generative adversarial networks (GANs), a recently introduced deep learning technique. A pre- and postprocessing pipeline allows using GANs for the generation of road networks. An in-depth evaluation shows that GANs faithfully learn the road structure present in the example network and that graph measures such as area, aspect ratio, and compactness, are maintained within the virtual road networks. To fill empty city blocks in road networks we propose two novel techniques. The first algorithm re-uses real-world city blocks and synthesizes building footprint layouts into empty city blocks by retrieving viable candidate blocks from a database. We evaluate the algorithm and synthesize a multitude of city block layouts reusing real-world building footprint arrangements from European and US-cities. In addition, we increase the realism of the synthesized layouts by performing example-based placement of 3D building models. This technique is evaluated by placing buildings onto challenging footprint layouts using different example building databases. The second algorithm computes a city block layout, resembling the style of a real-world city block. The original footprint layout is deformed to construct a textit{guidance map}, i.e., the original layout is transferred to a target city block using warping. This guidance map and the original footprints are used by an optimization technique that computes a novel footprint layout along the city block edges. We perform a detailed evaluation and show that using the guidance map allows transferring of the original layout, locally as well as globally, even when the source and target shapes drastically differ. To synthesize individual buildings, we use the general optimization technique described first and formulate the building generation process as a resource-constrained optimization problem. From an input database of annotated building parts, an abstract description of the building shape, and the specification of resource constraints such as length, area, or a number of architectural elements, a novel building is synthesized. We evaluate the technique by synthesizing a multitude of challenging buildings fulfilling several global and local resource constraints. Finally, we show how this technique can even be used to synthesize buildings having the shape of city blocks and might also be used to fill empty city blocks in virtual street networks. All algorithms presented in this work were developed to work with a small amount of user input. In most cases, simple sketches and the definition of constraints are enough to produce plausible results. Manual work is necessary to set up the building part databases and to download example data from mapping services available on the Internet

Intelligent Generation of Graphical Game Assets: A Conceptual Framework and Systematic Review of the State of the Art

Procedural content generation (PCG) can be applied to a wide variety of tasks in games, from narratives, levels and sounds, to trees and weapons. A large amount of game content is comprised of graphical assets, such as clouds, buildings or vegetation, that do not require gameplay function considerations. There is also a breadth of literature examining the procedural generation of such elements for purposes outside of games. The body of research, focused on specific methods for generating specific assets, provides a narrow view of the available possibilities. Hence, it is difficult to have a clear picture of all approaches and possibilities, with no guide for interested parties to discover possible methods and approaches for their needs, and no facility to guide them through each technique or approach to map out the process of using them. Therefore, a systematic literature review has been conducted, yielding 200 accepted papers. This paper explores state-of-the-art approaches to graphical asset generation, examining research from a wide range of applications, inside and outside of games. Informed by the literature, a conceptual framework has been derived to address the aforementioned gaps

DeepGlobe 2018: A Challenge to Parse the Earth through Satellite Images

We present the DeepGlobe 2018 Satellite Image Understanding Challenge, which includes three public competitions for segmentation, detection, and classification tasks on satellite images. Similar to other challenges in computer vision domain such as DAVIS and COCO, DeepGlobe proposes three datasets and corresponding evaluation methodologies, coherently bundled in three competitions with a dedicated workshop co-located with CVPR 2018. We observed that satellite imagery is a rich and structured source of information, yet it is less investigated than everyday images by computer vision researchers. However, bridging modern computer vision with remote sensing data analysis could have critical impact to the way we understand our environment and lead to major breakthroughs in global urban planning or climate change research. Keeping such bridging objective in mind, DeepGlobe aims to bring together researchers from different domains to raise awareness of remote sensing in the computer vision community and vice-versa. We aim to improve and evaluate state-of-the-art satellite image understanding approaches, which can hopefully serve as reference benchmarks for future research in the same topic. In this paper, we analyze characteristics of each dataset, define the evaluation criteria of the competitions, and provide baselines for each task.Comment: Dataset description for DeepGlobe 2018 Challenge at CVPR 201