66 research outputs found

    A greedy heuristic for axial line placement in collections of convex polygons

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    Master of Science - ScienceAxial line placement is one step in a method known as space syntax which is used in town planning to analyse architectural structures. This is becoming increasingly important in the quickly growing urban world of today. The field of axial line placement is an area of space syntax that has previously been done manually which is becoming increasingly impractical. Research is underway to automate the process and this research forms a large part of the automation. The general problem of axial line placement has been shown to be NP-complete. For this reason, previous research in this field has been focused on finding special cases where this is not the case or finding heuristics that approximate a solution. The majority of the research conducted has been on the simpler case of axial line placement in configurations of orthogonal rectangles and the only work done with convex polygons has been in the restricted case of deformed urban grids. This document presents research that finds two non-trivial special cases of convex polygons that have polynomial solutions and finds the first heuristic for general configurations of convex polygons

    Single-crossing orthogonal axial lines in orthogonal rectangles

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    The axial map of a town is one of the key components of the space syntax method – a tool for analysing urban layout. It is derived by placing the longest and fewest lines, called axial lines, to cross the adjacencies between convex polygons in a convex map of a town. Previous research has shown that placing axial lines to cross the adjacencies between a collection of convex polygons is NP-complete, even when the convex polygons are restricted to rectangles and the axial lines to have orthogonal orientation. In this document, we show that placing orthogonal axial lines in orthogonal rectangles where the adjacencies between the rectangles are restricted to be crossed only once (ALPSC- OLOR) is NP-complete. As a result, we infer the single adjacency crossing version of the general axial line placement problem is NP-complete. The transformation of NPcompleteness of ALP-SC-OLOR is from vertex cover for biconnected planar graphs. A heuristic is then presented that gives a reasonable approximate solution to ALP-SC-OLOR based on a greedy method

    Overview of database projects

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    The use of entity and object oriented data modeling techniques for managing Computer Aided Design (CAD) is explored

    Automated generation of geometrically-precise and semantically-informed virtual geographic environnements populated with spatially-reasoning agents

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    La Géo-Simulation Multi-Agent (GSMA) est un paradigme de modélisation et de simulation de phénomènes dynamiques dans une variété de domaines d'applications tels que le domaine du transport, le domaine des télécommunications, le domaine environnemental, etc. La GSMA est utilisée pour étudier et analyser des phénomènes qui mettent en jeu un grand nombre d'acteurs simulés (implémentés par des agents) qui évoluent et interagissent avec une représentation explicite de l'espace qu'on appelle Environnement Géographique Virtuel (EGV). Afin de pouvoir interagir avec son environnement géographique qui peut être dynamique, complexe et étendu (à grande échelle), un agent doit d'abord disposer d'une représentation détaillée de ce dernier. Les EGV classiques se limitent généralement à une représentation géométrique du monde réel laissant de côté les informations topologiques et sémantiques qui le caractérisent. Ceci a pour conséquence d'une part de produire des simulations multi-agents non plausibles, et, d'autre part, de réduire les capacités de raisonnement spatial des agents situés. La planification de chemin est un exemple typique de raisonnement spatial dont un agent pourrait avoir besoin dans une GSMA. Les approches classiques de planification de chemin se limitent à calculer un chemin qui lie deux positions situées dans l'espace et qui soit sans obstacle. Ces approches ne prennent pas en compte les caractéristiques de l'environnement (topologiques et sémantiques), ni celles des agents (types et capacités). Les agents situés ne possèdent donc pas de moyens leur permettant d'acquérir les connaissances nécessaires sur l'environnement virtuel pour pouvoir prendre une décision spatiale informée. Pour répondre à ces limites, nous proposons une nouvelle approche pour générer automatiquement des Environnements Géographiques Virtuels Informés (EGVI) en utilisant les données fournies par les Systèmes d'Information Géographique (SIG) enrichies par des informations sémantiques pour produire des GSMA précises et plus réalistes. De plus, nous présentons un algorithme de planification hiérarchique de chemin qui tire avantage de la description enrichie et optimisée de l'EGVI pour fournir aux agents un chemin qui tient compte à la fois des caractéristiques de leur environnement virtuel et de leurs types et capacités. Finalement, nous proposons une approche pour la gestion des connaissances sur l'environnement virtuel qui vise à supporter la prise de décision informée et le raisonnement spatial des agents situés

    Efficient Decision Support Systems

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    This series is directed to diverse managerial professionals who are leading the transformation of individual domains by using expert information and domain knowledge to drive decision support systems (DSSs). The series offers a broad range of subjects addressed in specific areas such as health care, business management, banking, agriculture, environmental improvement, natural resource and spatial management, aviation administration, and hybrid applications of information technology aimed to interdisciplinary issues. This book series is composed of three volumes: Volume 1 consists of general concepts and methodology of DSSs; Volume 2 consists of applications of DSSs in the biomedical domain; Volume 3 consists of hybrid applications of DSSs in multidisciplinary domains. The book is shaped decision support strategies in the new infrastructure that assists the readers in full use of the creative technology to manipulate input data and to transform information into useful decisions for decision makers

    Data-driven Modelling of Shape Structure

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    In recent years, the study of shape structure has shown great promise, by taking steps towards exposing shape semantics and functionality to algorithms spanning a wide range of areas in computer graphics and vision. By shape structure, we refer to the set of parts that make a shape, the relations between these parts, and the ways in which they correspond and vary between shapes of the same family. These developments have been largely driven by the abundance of 3D data, with collections of 3D models becoming increasingly prominent and websites such as Trimble 3D Warehouse offering millions of free 3D models to the public. The ability to use large amounts of data inside these shape collections for discovering shape structure has made novel approaches to acquisition, modelling, fabrication, and recognition of 3D objects possible. Discovering and modelling the structure of shapes using such data is therefore of great importance. In this thesis we address the problem of discovering and modelling shape structure from large, diverse and unorganized shape collections. Our hypothesis is that by using the large amounts of data inside such shape collections we can discover and model shape structure, and thus use such information to enable structure-aware tools for 3D modelling, including shape exploration, synthesis and editing. We make three key contributions. First, we propose an efficient algorithm for co-aligning large and diverse collections of shapes, to tackle the first challenge in detecting shape structure, which is to place shapes in a common coordinate frame. Then, we introduce a method to parameterize shapes in terms of locations and sizes of their parts, and we demonstrate its application to concurrently exploring a shape collection and synthesizing new shapes. Finally, we define a meta-representation for a shape family, which models the relations of shape parts to capture the main geometric characteristics of the family, and we demonstrate how it can be used to explore shape collections and intelligently edit shapes

    Artistic Content Representation and Modelling based on Visual Style Features

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    This thesis aims to understand visual style in the context of computer science, using traditionally intangible artistic properties to enhance existing content manipulation algorithms and develop new content creation methods. The developed algorithms can be used to apply extracted properties to other drawings automatically; transfer a selected style; categorise images based upon perceived style; build 3D models using style features from concept artwork; and other style-based actions that change our perception of an object without changing our ability to recognise it. The research in this thesis aims to provide the style manipulation abilities that are missing from modern digital art creation pipelines
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