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Query Processing in 3D Spatial Databases: Experiences with Oracle Spatial 11g

  • Siva Ravada
  • Baris M. Kazar
  • Ravi Kothuri
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)

Abstract

Falling costs in laser scanning equipment have made it easier to acquire 3D representations of real world entities as high-density point clouds, which may then be generalized to compact forms such as TINs, meshes, surfaces and solids. Scaling to the sizes of such large point clouds is becoming increasingly impossible for desktop applications. Sensing the need for a scalable database management of such 3D data, Oracle developed the 3D Spatial Engine in Oracle 11g. In this paper, we first present the overall architecture and functionality of the 3D Spatial Engine and introduce new geo-referenced data types for scalable storage and management of point clouds, TINs, and 3D vector geometries. We then focus on efficient processing of queries on these data types using a 2-stage filtering. For the second-stage filtering on 3D data, we propose and evaluate various techniques for efficiently answering different types of 3D queries such as anyinteract and distance. We note that to compare the points of point-cloud block or TIN block efficiently with the query, a spatial index may be useful but the creation cost is high. Our experiences are as follows: (1) For an anyinteract query, R-tree based processing is only required when both data and query geometries have large numbers of sub-elements. (2) For a distance query, an R-tree based evaluation is always helpful. We also propose a novel vertex-avoiding ray shooting algorithm for the point-in-solid function.

Keywords

Point Cloud Query Processing Query Time Spatial Index Query Object 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Stoter J. and Zlatanova, S., 3D GIS, where are we standing, In: Joint Workshop on Spatial, Temporal and Multi-Dimensional Data Modelling and Analysis, Quebec city, 2003, Canada, 6p.Google Scholar
  2. 2.
    Penninga, F., van Oosterom, P. & Kazar, B. M., A TEN-based DBMS approach for 3D Topographic Data Modelling, International Symposium on Spatial Data Handling, Vienna, 2006, pages 581-598.Google Scholar
  3. 3.
    Zlatanova, S., On 3D Topological Relationships, 11th International Workshop on Database and Expert Systems Applications (DEXA), 2000, pages 913-919.Google Scholar
  4. 4.
    Mirtich, B., Fast and accurate computation of polyhedral mass properties, Journal of Graphics Tools, 1996, pages 31-50.Google Scholar
  5. 5.
    Kothuri, R. and Ravada, S., Sharma, J., Banerjee, J., Indexing Medium Dimensionality Data in Oracle, ACM SIGMOD, 1999.Google Scholar
  6. 6.
    Beckmann, N., Kriegel, H., Schneider, R. and Seeger, B., The R* tree: An efficient and robust access method for points and rectangles. In Proc. ACM SIGMOD Int. Conf. on Management of Data, pages 322-331, 1990.Google Scholar
  7. 7.
    Brinkhof, T., Kriegel, H., and Seeger, B., Efficient processing of spatial joins using R-trees. In Proc. ACM SIGMOD Int. Conf. on Management of Data, pages 237-246, 1994.Google Scholar
  8. 8.
    Gustavo Alonso, Fabio Casati, Web Services and Service-Oriented Architectures, ICDE 2005, p. 1147.Google Scholar
  9. 9.
    H. Samet, The Design and Analysis of Spatial Data Structures, Addison-Wesley, 1989.Google Scholar
  10. 10.
    The X3D Specification. www.web3d.org/x3d/specificationsGoogle Scholar
  11. 11.
    Kothuri, R., Ravada, S., Efficient processing of large spatial queries using interior approximations, Symposium on Spatio-Temporal Databases, SSTD, 2001.Google Scholar
  12. 12.
    Schneider, P. and Eberly, D., Geometric tools for computer graphics, MorganKaufmann Publishers, 2003.Google Scholar
  13. 13.
    Van den Bergen, G., Collision detection in interactive 3D environments, Morgan-Kaufmann, 2004.Google Scholar
  14. 14.
    Hans Plum. “3D City Models for Berlin, Bonn and Hamburg based on Open Source Software and Open Standards", Free and Open Source Software for GeoSpatial, Victoria, Canada, 2007.Google Scholar
  15. 15.
    Remondino Fabio. "From Point Cloud to Surface: The Modeling and Visualization problem", International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXIV-5/W10. International Workshop on Visualization and Animation of Reality-based 3D Models, 24-28 February 2003, Tarasp-Vulpera, Switzerland.Google Scholar
  16. 16.
    Ravi Kothuri, Albert Godfrind, Euro Beinat. “Pro Oracle Spatial 11g", Apress, 2nd Edition, Nov 2007.Google Scholar
  17. 17.
    David Mount. “On Geometric Intersection". The Handbook of Discrete and Computational Geometry, 2nd Edition, eds. J. E. Goodman and J. O’Rourke, Chapman & Hall/CRC, Boca Raton, pages 857-876, 2004.Google Scholar
  18. 18.
    M. Pellegrini, Ray shooting and lines in space, Handbook of discrete and computational geometry, ed. Goodman, O’Rourke, 2nd ed. 2004, pages 239-256.Google Scholar
  19. 19.
    Oracle Database 11g Release 1 Documentation. http://www.oracle.com/technology/documentation/database.htmlGoogle Scholar
  20. 20.
    Baris Kazar, Ravi Kothuri, Siva Ravada, On Valid and Invalid Three-Dimensional Geometries, 2nd International Workshop on 3D Geo-Information, Netherlands, pages 19-46, 2007.Google Scholar
  21. 21.
    Martin Isenburg, Yuanxin Liu, Jonathan Shewchuk, Jack Snoeyink, Streaming Computation of Delaunay Triangulations, Proceedings of SIGGRAPH’06, pages 1049-1056, July 2006.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Siva Ravada
    • 1
  • Baris M. Kazar
    • 1
  • Ravi Kothuri
    • 1
  1. 1.Oracle USA Inc.USA

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