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Folkioneer: Efficient Browsing of Community Geotagged Images on a Worldwide Scale

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MultiMedia Modeling (MMM 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8326))

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Abstract

In this paper, we introduce Folkioneer, a novel approach for browsing and exploring community-contributed geotagged images. Initially, images are clustered based on the embedded geographical information by applying an enhanced version of the CURE algorithm, and characteristic geodesic shapes are derived using Delaunay triangulation. Next, images of each geographical cluster are analyzed and grouped according to visual similarity using SURF and restricted homography estimation. At the same time, LDA is used to extract representative topics from the provided tags. Finally, the extracted information is visualized in an intuitive and user-friendly manner with the help of an interactive map.

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References

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Author information

Authors and Affiliations

  1. Universität Passau, Innstr. 43, 94032, Passau, Germany

    Hatem Mousselly-Sergieh, Daniel Watzinger, Bastian Huber & Harald Kosch

  2. Université Lyon, 20 Av. Albert Einstein, 69621, Villeurbanne, France

    Hatem Mousselly-Sergieh & Elöd Egyed-Zsigmond

  3. FH Kufstein, Andreas Hofer-str. 7, 6330, Kufstein, Austria

    Mario Döller

Authors
  1. Hatem Mousselly-Sergieh
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  2. Daniel Watzinger
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  3. Bastian Huber
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  4. Mario Döller
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  5. Elöd Egyed-Zsigmond
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  6. Harald Kosch
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Editor information

Editors and Affiliations

  1. School of Computing, Dublin City University, 9, Dublin, Ireland

    Cathal Gurrin

  2. Fakultät IV für Elektrotechnik und Informatik, Technische Universität Berlin / DAI-Labor, 10587, Berlin, Germany

    Frank Hopfgartner

  3. Department of Information and Computing Sciences, Universiteit Utrecht, 3584, Utrecht, CC, The Netherlands

    Wolfgang Hurst

  4. UiT The Arctic University of Norway, 9019, Tromsø, Norway

    Håvard Johansen

  5. Singapore University of Technology and Design, Singapore

    Hyowon Lee

  6. School of Electrical Engineering, Dublin City University, Ireland

    Noel O’Connor

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© 2014 Springer International Publishing Switzerland

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Mousselly-Sergieh, H., Watzinger, D., Huber, B., Döller, M., Egyed-Zsigmond, E., Kosch, H. (2014). Folkioneer: Efficient Browsing of Community Geotagged Images on a Worldwide Scale. In: Gurrin, C., Hopfgartner, F., Hurst, W., Johansen, H., Lee, H., O’Connor, N. (eds) MultiMedia Modeling. MMM 2014. Lecture Notes in Computer Science, vol 8326. Springer, Cham. https://doi.org/10.1007/978-3-319-04117-9_36

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  • DOI: https://doi.org/10.1007/978-3-319-04117-9_36

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-04116-2

  • Online ISBN: 978-3-319-04117-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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