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A Modeling and Similarity Measure Function for Multiple Trajectories in Moving Databases

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Computational Science and Its Applications - ICCSA 2006 (ICCSA 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3981))

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Abstract

In this paper, we focus on a new spatio-temporal representation scheme which can efficiently model multiple trajectories based on several moving objects in video databases. The traditional methods only consider direction property, time interval property, and spatial relations property for modeling moving objects’ trajectories. But, our method also takes into account on distance property, conceptual location information, and related object information (e.g. player name having a soccer ball). In addition, we propose a similarity measure function that improves a retrieval accuracy to measure a similarity among multiple trajectories. The proposed scheme supports content-based retrieval using moving objects’ trajectories and supports semantics-based retrieval using concepts which are acquired through the location information of moving objects. Finally, from the experimental results using real trajectories extracted from soccer video data with soccer ball and player, the performance of our scheme achieves about 15-20% performance improvement against existing schemes when the weights of angle and topological relation are over two times than that of distance.

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Author information

Authors and Affiliations

  1. School of Information & Communication Engineering, Sunchon National University, Suncheon, Jeonnam, 540-742, South Korea

    Choon-Bo Shim & John Kim

Authors
  1. Choon-Bo Shim
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  2. John Kim
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Calgary, 2500 University Drive N.W., T2N 1N4, Calgary, AB, Canada

    Marina L. Gavrilova

  2. Department of Mathematics and Computer Science, University of Perugia, via Vanvitelli, 1, I-06123, Perugia, Italy

    Osvaldo Gervasi

  3. William Norris Professor, Head of the Computer Science and Engineering Department, University of Minnesota, USA

    Vipin Kumar

  4. OptimaNumerics Ltd., Cathedral House, 23-31 Waring Street, BT1 2DX, Belfast, UK

    C. J. Kenneth Tan

  5. Clayton School of IT, Monash University, 3800, Clayton, Australia

    David Taniar

  6. Department of Chemistry, University of Perugia, Via Elce di Sotto, 8, I-06123, Perugia, Italy

    Antonio Laganá

  7. School of Computing, Soongsil University, Seoul, Korea

    Youngsong Mun

  8. School of Information and Communication Engineering, Sungkyunkwan University, Korea

    Hyunseung Choo

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© 2006 Springer-Verlag Berlin Heidelberg

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Shim, CB., Kim, J. (2006). A Modeling and Similarity Measure Function for Multiple Trajectories in Moving Databases. In: Gavrilova, M.L., et al. Computational Science and Its Applications - ICCSA 2006. ICCSA 2006. Lecture Notes in Computer Science, vol 3981. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11751588_13

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  • DOI: https://doi.org/10.1007/11751588_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34072-0

  • Online ISBN: 978-3-540-34074-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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