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A Grid-Based Index and Queries for Large-Scale Geo-tagged Video Collections

  • He Ma
  • Sakire Arslan Ay
  • Roger Zimmermann
  • Seon Ho Kim
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7240)

Abstract

Currently a large number of user-generated videos are produced on a daily basis. It is further increasingly common to combine videos with a variety of meta-data that increase their usefulness. In our prior work we have created a framework for integrated, sensor-rich video acquisition (with one instantiation implemented in the form of smartphone applications) which associates a continuous stream of location and direction information with the acquired videos, hence allowing them to be expressed and manipulated as spatio-temporal objects. In this study we propose a novel multi-level grid-index and a number of related query types that facilitate application access to such augmented, large-scale video repositories. Specifically our grid-index is designed to allow fast access based on a bounded radius and viewing direction – two criteria that are important in many applications that use videos. We present performance results with a comparison to a multi-dimensional R-tree implementation and show that our approach can provide significant speed improvements of at least 30%, considering a mix of queries.

Keywords

Query Processing Voronoi Diagram Index Structure Range Query Video Segment 
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.
  2. 2.
  3. 3.
    Arslan Ay, S., Zimmermann, R., Kim, S.: Viewable Scene Modeling for Geospatial Video Search. In: ACM Int’l Conference on Multimedia, pp. 309–318 (2008)Google Scholar
  4. 4.
    Arslan Ay, S., Zimmermann, R., Kim, S.H.: Generating Synthetic Meta-data for Georeferenced Video Management. In: ACM SIGSPATIAL Int’l Conference on Advances in Geographic Information Systems, GIS (2010)Google Scholar
  5. 5.
    Beckmann, N., Kriegel, H., Schneider, R., Seeger, B.: The R*-tree: An Efficient and Robust Access Method for Points and Rectangles. In: ACM SIGMOD Int’l Conference on Management of Data, pp. 322–331 (1990)Google Scholar
  6. 6.
    Eppstein, D., Goodrich, M., Sun, J.: The Skip Quadtree: A Simple Dynamic Data Structure for Multidimensional Data. In: Annual Symposium on Computational Geometry (2005)Google Scholar
  7. 7.
    Finkel, R., Bentley, J.: Quad Trees: A Data Structure for Retrieval on Composite Keys. Acta Informatica 4(1), 1–9 (1974)zbMATHCrossRefGoogle Scholar
  8. 8.
    Graham, C.: Vision and Visual Perception (1965)Google Scholar
  9. 9.
    Guttman, A.: R-Trees: A Dynamic Index Structure for Spatial Searching. In: ACM SIGMOD Int’l Conference on Management of Data (1984)Google Scholar
  10. 10.
    Hwang, T., Choi, K., Joo, I., Lee, J.: MPEG-7 Metadata for Video-based GIS Applications. In: IEEE Int’l Geoscience and Remote Sensing Symposium (2004)Google Scholar
  11. 11.
    Kim, K., Kim, S., Lee, S., Park, J., Lee, J.: The Interactive Geographic Video. In: IEEE Int’l Geoscience and Remote Sensing Symposium (IGARSS), vol. 1, pp. 59–61 (2003)Google Scholar
  12. 12.
    Kim, S., Arslan Ay, S., Yu, B., Zimmermann, R.: Vector Model in Support of Versatile Georeferenced Video Search. In: ACM SIGMM Conference on Multimedia Systems (2010)Google Scholar
  13. 13.
    Liu, X., Corner, M., Shenoy, P.: SEVA: Sensor-Enhanced Video Annotation. In: ACM Int’l Conference on Multimedia, pp. 618–627 (2005)Google Scholar
  14. 14.
    Ma, H., Arslan Ay, S., Zimmermann, R., Kim, S.H.: Metadata Organization and Query Optimization for Large-scale Geo-tagged Video Collections. NUS/SoC Technical Report TR10/11, National University of Singapore (October 2011)Google Scholar
  15. 15.
    Nutanong, S., Zhang, R., Tanin, E., Kulik, L.: The V*-Diagram: A Query-dependent Approach to Moving KNN Queries. Proceedings of the VLDB Endowment 1(1), 1095–1106 (2008)Google Scholar
  16. 16.
    Okabe, A.: Spatial Tessellations: Concepts and Applications of Voronoi Diagrams. John Wiley & Sons Inc. (2000)Google Scholar
  17. 17.
    Rigaux, P., Scholl, M., Voisard, A.: Spatial Databases with Application to GIS. SIGMOD Record 32(4), 111 (2003)CrossRefGoogle Scholar
  18. 18.
    Roussopoulos, N., Faloutsos, C., Timos, S.: The R + -tree: A Dynamic Index for Multi-dimensional Objects. In: Int’l Conference on Very Large Databases (VLDB), pp. 507–518 (1987)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • He Ma
    • 1
  • Sakire Arslan Ay
    • 1
  • Roger Zimmermann
    • 1
  • Seon Ho Kim
    • 2
  1. 1.School of ComputingNational University of SingaporeSingaporeSingapore
  2. 2.Integrated Media Systems CenterUniversity of Southern CaliforniaLAUSA

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