UDMV: EG Workshop on Urban Data Modelling and Visualisation

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Browsing UDMV: EG Workshop on Urban Data Modelling and Visualisation by Subject "Curve"

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    Automated Production of Interactive 3D Temporal Geovisualizations so as to Enhance Flood Risk Awareness
    (The Eurographics Association, 2016) Jacquinod, Florence; Pedrinis, Frédéric; Edert, Jérémy; Gesquière, Gilles; Vincent Tourre and Filip Biljecki
    The FLOOD AR project originates from an explicitly expressed need for digital 3D temporal georeferenced models that can be largely diffused among riverside residents through computers and mobile devices, in order to support the raising of public awareness concerning flood risk along the Rhône river. This project is led by a multidisciplinary consortium of researchers from several fields who are working together to develop usable tools and models as well as recommendations regarding visual content, interfaces and context of use for those 3D models. As far as computer science is concerned, given the practical difficulties of resorting to 3D georeferenced technologies for practitioners and the current limitations of commonly used GIS data formats and tools, automatic tools allowing any interested parties to produce 3D temporal models in order to support flood risk awareness' enhancement were developed in the first phase of the project. The storage of those 3D models in an interoperable format (CityGML) ensures that those 3D temporal models are available for other purposes in relation to flood mitigation (regarding flood risk mitigation planning and public consultations or visual analysis for instance). Automating the production of 3D temporal models guarantees that those models can be produced for any territory along the Rhône river. A tool to visualize those 3D temporal models interactively will also be made available as an open source tool as part of the project.
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    Indoor Scene Reconstruction using Primitive-driven Space Partitioning and Graph-cut
    (The Eurographics Association, 2013) Oesau, Sven; Lafarge, Florent; Alliez, Pierre; Vincent Tourre and Gonzalo Besuievsky
    We present a method for automatic reconstruction of permanent structures of indoor scenes, such as walls, floors and ceilings, from raw point clouds acquired by laser scanners. Our approach employs graph-cut to solve an inside/outside labeling of a space decomposition. To allow for an accurate reconstruction the space decomposition is aligned with permanent structures. A Hough Transform is applied for extracting the wall directions while allowing a flexible reconstruction of scenes. The graph-cut formulation takes into account data consistency through an inside/outside prediction for the cells of the space decomposition by stochastic ray casting, while favoring low geometric complexity of the model. Our experiments produces watertight reconstructed models of multi-level buildings and complex scenes.