View-Dependent Simplification of Complex Urban Scenes Using Weighted Quadtrees

  • Bum-Jong Lee
  • Jong-Seung Park
  • Mee Young Sung
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4282)


This article describes a new contribution culling method for the view-dependent real-time rendering of complex huge urban scenes. As a preprocessing step, the view frustum culling technique is used to cull away invisible objects that are outside the view frustum. For the management of the levels-of-detail, we subdivide the image regions and construct a weighted quadtree. The weight of each quadtree node is defined as the sum of weights of all objects contained in the node or its child nodes. The weight of an object is proportional to the view space area of the projected object as well as the distance from the viewpoint. Hence, large buildings in the far distance are not always culled out since their contributions to the rendering quality can be larger than those of near small buildings. We tested the proposed method by applying it to render a huge number of structures in our metropolitan section which is currently under development. Experimental results showed that the proposed rendering method guarantees real-time rendering of complex huge scenes.


Child Node Camera Angle Screen Space World Space Urban Scene 
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  1. 1.
    Tsuji, T., Zha, H., Kurazume, R., Hasegawa, T.: Interactive rendering with lod control and occlusion culling based on polygon hierarchies. In: Proceedings of the Computer Graphics International (CGI 2004), pp. 536–539 (2004)Google Scholar
  2. 2.
    Akenine-Möller, T., Haines, E.: Real-Time Rendering. A. K. Peters, Ltd., Natick (2002)Google Scholar
  3. 3.
    Assarsson, U., Moller, T.: Optimized view frustum culling algorithms for bounding boxes. Journal of Graphics Tools 5(1), 9–22 (2000)CrossRefGoogle Scholar
  4. 4.
    Samet, H., Webber, R.E.: Hierarchical data structures and algorithms for computer graphics. i. fundamentals. IEEE Computer Graphics and Application 8, 48–68 (1988)CrossRefGoogle Scholar
  5. 5.
    Falby, J.S., Zyda, M.J., Pratt, D.R., Mackey, R.L.: Npsnet: Hierarchical data structures for real-time three-dimensional visual simulation. Computers and Graphics 17(1), 65–69 (1993)CrossRefGoogle Scholar
  6. 6.
    Pajarola, R.: Large scale terrain visualization using the restricted quadtree triangulation. In: Proceedings of IEEE Visualization 1998, pp. 19–24 (1998)Google Scholar
  7. 7.
    Gudukbay, U., Yilmaz, T.: Stereoscopic view-dependent visualization of terrain height fields. IEEE Transactions on Visualization and Computer Graphics 8(4), 330–345 (2002)CrossRefGoogle Scholar
  8. 8.
    Yin, P., Shi, J.: Cluster based real-time rendering system for large terrain dataset. Computer Aided Design and Computer Graphics, 365–370 (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Bum-Jong Lee
    • 1
  • Jong-Seung Park
    • 1
  • Mee Young Sung
    • 1
  1. 1.Department of Computer Science & EngineeringUniversity of IncheonIncheonRepublic of Korea

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