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Geoinformatik

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Quantitative Methods vor Visual Computing Quantitative Methods vor Visual Computing (SFB TRR 161)

The overall goal of the Collaborative Research Center is establishing the paradigm of quantitative science in visual computing. In several directions it will provide conceptual and tangible contributions, including conceptual metrics and models for quantification, new techniques and algorithms for visual computing, respective software, benchmark data that can be used for quantitative evaluation, and improved evaluation methodology. More ...


Crowd-sourced Indoor Modelling Crowd-sourced Indoor Modelling

Humans spend today most of their time indoors and they need location based facilities, especially in public buildings. However, a large amount of indoor space is unmapped. An innovative solution for this issue is to exploit the data that is already available, coming from mobile devices. Despite being indispensable tools for everyday life, they are a meaningful source of information supported by powerful sensors and increasing computational power. In this way, ComNSense project has the purpose of using the mobile data coming from the crowd, for automatically mapping indoor environments. Therefore, it is assumed that mobile device users are walking through public indoor environments and send the acquired data to a server for modeling the 3D space. The server has also to send quality indictors back to the users and to direct them to the locations where the obtained model is suffering of a lack of information. More ...


Data Model for Hybrid 3D Geoinformation Systems Data Model for Hybrid 3D Geoinformation Systems

Recent trends in the area of geoinformatics attest to the considerable change in data acquisition and data processing that can currently be recognized: rapidly advancing developments of new sensor technologies for both highly specialized measuring systems and low-cost devices account for the tremendous increase in the availability of 3D geodata. However, there is still a lack of appropriate tools for integrated data management and analysis solutions that can cope with the great diversity of 3D geodata. Thus, we deal with the development of a hybrid 3D geoinformation system which is able to combine and analyse heterogeneous 3D geodata in an efficient and consistent way. More ...


Automatic Map Retrieval in the Internet Automatic Map Retrieval in the Internet

The internet contains huge amounts of maps representing almost every part of the Earth in many different scales and map types. However, this enormous quantity of information is completely unstructured and it is very difficult to find a map of a specific area and with certain content, because the map content is not accessible by search engines in the same way as web pages. However, searching with search engines is at the moment the most effective way to retrieve information in the internet and without search engines most information would not be findable. In order to overcome this problem, methods are needed to search automatically for maps in the internet and to make the implicit information of maps explicit so that it can be processed by machines. More ...


Quality Evaluation of Generalized Building Footprints Quality Evaluation of Generalized Building Footprints

Generalization operators are difficult to formalize: each different generalization approach represents its own and unique implementation. Therefore, different generalizations of the same object are possible which can change the geometry of the object in different ways. The objective of this research consists in proposing a generic quality evaluation framework for generalization operators. It aims to assess the quality of generalized building groundplans both on level of single objects and data sets and enables the comparison of generalization alternatives. More ...


Grammar Supported Façade Reconstruction Grammar Supported Façade Reconstruction

Frequently, algorithms for 3D facade reconstruction extract high resolution building geometry like windows, doors and protrusions from terrestrial LiDAR and image data. However, such a bottom-up modelling of facade structures is only feasible if the observed data meets considerable requirements on data quality. Errors in measurement, varying point densities, reduced accuracies, as well as incomplete coverage affect the achievable correctness and reliability of the reconstruction result. For this reason, we enhance the explicit reconstruction of facades by the integration of rules. The rules are derived automatically from already reconstructed facades, which serve as knowledge base for further processing. They are used for the verification of the facade model produced during the data driven reconstruction process and the generation of synthetic facades for which only partially or no sensor data is available. More ...


Context Information from Detailed Façade Models Context Information from Detailed Façade Models

In order to provide a geometric basis for spatial world models for context aware applications, methods for the automatic derivation of 3D building structures from sensor data with heterogeneous quality have been developed. Resulting 3D building models can be used for various scenarios. Strategies have been worked out to make the 3D building structures applicable in navigation systems for blind people. Based on façade models in which detailed façade structures are represented by explicit 3D geometry and semantic information, 2D maps can be derived for each floor where windows and doors are described by annotated polygons. More ...


Generalization of 2D and 3D Data Generalization of 2D and 3D Data

Generalisation is a process to transform spatial data from a detailed scale into a less detailed scale. Unlike the geometric simplification, generalisation does not only decrease the complexity and data volume, but also improves the cognitive perceptibility of spatial situations for cartographic presentations. This is comparable to how maps work. If we want to draw the attention of a user to a specific building, we can visualise its surrounding area with generalised models, whereas the important building is presented in its original or even highlighted shape. More ...


Conflation of Spatial Data Conflation of Spatial Data

Along with the increasing power of Geographical Information Systems (GIS) there is an increasing demand for spatial data. National and private institutions collect spatial data in different data models and scales in order to meet this demand. Additionally, huge amounts of spatial data are collected in Web 2.0 mapping portals. The result is a multiple representation of the same topographic objects of the landscape. The aim of this research is to investigate the integration of such datasets by using conflation techniques. Conflation is a kind of spatial data processing that combines multiple layers of spatial data into one common layer. More ...


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