UDMV13: Eurographics Workshop on Urban Data Modelling and Visualisation

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https://diglib.eg.org/handle/10.2312/451

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Browsing UDMV13: Eurographics Workshop on Urban Data Modelling and Visualisation by Subject "I.3.5 [Computer Graphics]"

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    Challenges and Ideas in Procedural Modeling of Interiors
    (The Eurographics Association, 2013) Ilcik, Martin; Wimmer, Michael; Vincent Tourre and Gonzalo Besuievsky
    While the creation of convincing cityscapes from the outside is already possible, there is a lack of robust and efficient techniques for modeling the interior of buildings. In particular, we focus on challenges for the subdivision of the interior space into rooms and for placement of furniture in those rooms.
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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.
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    Online Reconstruction of Textured Triangle Meshes from Aerial Images
    (The Eurographics Association, 2013) Vierjahn, Tom; Roters, Jan; Moser, Manuel; Hinrichs, Klaus; Mostafawy, Sina; Vincent Tourre and Gonzalo Besuievsky
    In this paper we present and evaluate a new online reconstruction algorithm to create a textured triangle mesh from a set of aerial images via an unorganized point cloud. Both the point cloud and the mesh are iteratively refined while allowing new aerial images to be added at any time during reconstruction. Texture coordinates are learnt to instantly visualize an initially rough approximation that gets refined as more data becomes available. The new algorithm improves upon other systems that require the complete data to be acquired beforehand, and that apply offline, non-iterative reconstruction and processing. Thus, our algorithm is perfectly suited for time-critical applications, e. g., strategical visualization platforms for disaster and emergency response.