Skip to main content

Advertisement

SpringerLink
Log in

Semantic visualization of 3D urban environments

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

The purpose of this work is the semantic visualization of complex 3D city models containing numerous dynamic entities, as well as performing interactive semantic walkthroughs and flights without predefined paths. This is achieved by using a 3D multilayer scene graph that integrates geometric and semantic information as well as by the performance of efficient geometric and what we call semantic view culling. The proposed semantic-geometric scene graph is a 3D structure composed of several layers which is suitable for visualizing geometric data with semantic meaning while the user is navigating inside the 3D city model. BqR-Tree is the data structure specially developed for the geometric layer for the purpose of speeding up rendering time in urban scenes. It is an improved R-Tree data structure based on a quadtree spatial partitioning which improves the rendering speed of the usual R-trees when view culling is implemented in urban scenes. The BqR-Tree is defined by considering the city block as the basic and logical unit. The advantage of the block as opposed to the traditional unit, the building, is that it is easily identified regardless of the data source format, and allows inclusion of mobile and semantic elements in a natural way. The usefulness of the 3D scene graph has been tested with low structured data, which makes its application appropriate to almost all city data containing not only static but dynamic elements as well.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  1. Andujar C, Díaz J, Brunet P (2008) Relief impostor selection for large scale urban rendering, IEEE Virtual Reality Workshop on Virtual Cityscapes: Key Research Issues in Modeling Large-Scale Immersive Urban Environments

  2. Assarsson U, Moller T (2000) Optimized view frustum culling algorithms for bounding boxes. J Graphics Tools 5(1):9–22

    Article  Google Scholar 

  3. Attene M, Robbiano F, Spagnuolo M, Falcidieno B (2009) Comput-Aided Des 41(10):756–763

    Article  Google Scholar 

  4. Benner J, Geiger A, Leinemann K (2005) Flexible generation of semantic 3D building models. 1st Intern. ISPRS/EuroSDR/DGPF-Workshop on Next Generation 3D City Models., 49

  5. Biermann, Peter and Frohlich, Christian and Latoschik, Marc and Wachsmuth, Ipke (2007) Semantic information and local constraints for parametric parts in interactive virtual construction, SG ‘07: Proceedings of the 8th international symposium on Smart Graphics, 124–134}

  6. Chakrabarti K, Mehrotra S (1999) The hybrid tree: an index structure for high dimensional feature spaces. In: Proc. Int. Conf. Data Engineering, pp 440–447

  7. Dollner J, Buchholz H (2005) Continuous level-of-detail modeling of buildings in 3D city models: Proceedings of the 13th annual ACM international workshop on Geographic information systems, Bremen, Germany, pp 173–181

  8. Falquet G, Métral C (2005) Integrating urban knowledge into 3D City Models. In: Proc. First International Workshop on Next Generation 3D City Models

  9. Gerhard R, Dieter S (2005) Flexible parameterization of scene graphs. In: Proceedings IEEE Virtual Reality Conference 2005 (VR‘05), pp 51–58

  10. Grundhöfer A, Brombach B, Scheibe R, Fröhlich B (2005) Level of detail based occlusion culling for dynamic scenes. In: Proceedings of the 3rd international Conference on Computer Graphics and interactive Techniques in Australasia and South East Asia,. GRAPHITE ‘05. ACM, pp 37–45

  11. Guttman A, Yormark B (1984) R-Trees: A Dynamic Index Structure for Spatial Searching, SIGMOD 84 Proceedings of Annual Meeting, Boston, Massachusetts, pp 47–57

  12. Katayama N, Shinichi S (1997) The {SR-Tree}: an index structure for high-dimensional nearest neighbour queries, Proceedings of ACM SIGMOD May 1997, pp 369–380

  13. Klima M, Halabala P, Slavik P (2004) Semantic information visualization, Semantic information visualization. CODATA Workshop Prague

  14. Lee B-J, Park J-S, Sung MY (2006) View-dependent simplification of complex urban scenes using weighted quadtrees. Adv Artif Real Tele Existence Springer Berlin 4282/2006:1243–1252

    Article  Google Scholar 

  15. Leissler M, Müller A, Hemmje M, Neuhold EA, Component VR (2000) Architecture for visual multi-user applications. In: ISCA 2nd International Conference on Information Reuse and Integration (IRI-2000)

  16. Li T, Hsu S (2004) An intelligent 3D user interface adapting to user control behaviors. In: Proceedings of the 9th international Conference on intelligent User interfaces. IUI ‘04. ACM Press, pp 184–190

  17. Manocha D (2008) Real-time motion planning for agent-based crowd simulation, Proceedings of 2008 IEEE Virtual Reality Workshop on Virtual Cityscapes

  18. Mendez E, Schall G, Havemann S, Junghanns S, Fellner D, Schmalstieg D (2008) Generating semantic 3D models of underground infrastructure. IEEE Comput Graph Appl 28(3):48–57

    Article  Google Scholar 

  19. Otto K (2005) Semantic virtual environments. In: Proceedings of the 14th international World Wide Web conference. ACM press, Chiba, Japan, pp 1036–1037

  20. Pina JL, Serón FJ, Cerezo E (2009) Efficient visualization of dynamic urban scenes iasted VIIP09. 652–044:1776–183

  21. Stadler A, KOLBE TH (2007) Spatio-semantic coherence in the integration of 3D city models. In: Proceedings of the 5th International Symposium on Spatial Data Quality ISSDQ

  22. Wald, Ingo, Ize, Thiago, Parker, Steven G (2008) Special section: parallel graphics and visualization: fast, parallel, and asynchronous construction of BVHs for ray tracing animated scenes. Comput Graph 32(1):3–13

    Article  Google Scholar 

  23. Xia Y, Prabhakar S (2003) Q + Rtree: efficient ndexing for moving object databases, Proceedings of the Eighth International Conference on Database Systems for Advanced Applications, pp 175

Download references

Acknowledgements

This work has been partly financed by the Spanish Dirección General de Investigación, contract number TIN2007-63025 and by the Government of Aragón by way of the WALQA agreement.

Author information

Authors and Affiliations

  1. Advanced Computer Graphics Group (GIGA), Computer Science Department, University of Zaragoza, Engineering Research Institute of Aragon (I3A), Zaragoza, Spain

    Jose Luis Pina, Eva Cerezo & Francisco Seron

Authors
  1. Jose Luis Pina
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Eva Cerezo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Francisco Seron
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jose Luis Pina.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Pina, J.L., Cerezo, E. & Seron, F. Semantic visualization of 3D urban environments. Multimed Tools Appl 59, 505–521 (2012). https://doi.org/10.1007/s11042-011-0776-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-011-0776-3

Keywords

Search

Navigation