Browsing UDMV13: Eurographics Workshop on Urban Data Modelling and Visualisation by Title

Now showing items 8-12 of 12

    • NightLighting: a Nocturnal Urban Illumination Approach 

      Muñoz-Pandiella, Imanol; Andújar, Carlos; Patow, Gustavo (The Eurographics Association, 2013)
      Real time rendering of cities with realistic global illumination is still an open problem. In this paper we propose a two-step algorithm to simulate the nocturnal illumination of a city. The first step computes an approximate ...

    • Online Reconstruction of Textured Triangle Meshes from Aerial Images 

      Vierjahn, Tom; Roters, Jan; Moser, Manuel; Hinrichs, Klaus; Mostafawy, Sina (The Eurographics Association, 2013)
      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 ...

    • Taking Advantage of Low Radiative Coupling in 3D Urban Models 

      Beckers, Benoit (The Eurographics Association, 2013)
      We examine different techniques able to enhance the efficiency of urban simulations. Condensation techniques like superelements - well known in the finite element community - are good candidates to improve the heat transfers ...

    • Toward Automated Façades Generation from Oblique Aerial Images 

      Vahl, Matthias; Lukas, Uwe von (The Eurographics Association, 2013)
      In this paper we introduce an approach for automatic recognition and description of building façades from oblique aerial images. This approach does not use street-side images, like Google StreetView, but aerial images to ...

    • Understanding City Dynamics through Spatio-temporal Visualization 

      Dias, Luís; Silva, Nelson; Cardoso, Tiago; Fonseca, Manuel J. (The Eurographics Association, 2013)
      Every time we visit a new city there is a huge effort made in understanding its dynamic, i.e. what are the relevant locations within that city in each time period, for there are large amounts of data to sift through. ...