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Georeferencing Flickr Resources Based on Multimodal Features

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Multimodal Location Estimation of Videos and Images

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Abstract

The popularity of social media, and location-based services in particular, has led to a vast increase in the number of georeferenced resources on the web.

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Notes

  1. 1.

    http://pressroom.yahoo.co.uk/pr/ycorpuk/flickr-tips-safer-photos.aspx, accessed 31 March 2014.

  2. 2.

    http://www.flickr.com/services/api/, accessed 28 January 2014.

  3. 3.

    \(13.6\,\%\) do not have any tags in the Placing task data set, although some of them can also be georeferenced by taking into account context information such as the home location of the user.

  4. 4.

    http://www.flickr.com/photos/88878784@N00/4706267893.

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Authors and Affiliations

  1. Technische Universität, Berlin, Germany

    Pascal Kelm, Sebastian Schmiedeke & Thomas Sikora

  2. Cardiff University, Cardiff, UK

    Steven Schockaert

  3. Yahoo Labs, Barcelona, Spain

    Michele Trevisiol & Olivier Van Laere

Authors
  1. Pascal Kelm
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  2. Sebastian Schmiedeke
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  3. Steven Schockaert
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  4. Thomas Sikora
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  5. Michele Trevisiol
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  6. Olivier Van Laere
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Correspondence to Pascal Kelm .

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Editors and Affiliations

  1. International Computer Science Institute, Berkeley, California, USA

    Jaeyoung Choi

  2. International Computer Science Institute, Berkeley, California, USA

    Gerald Friedland

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Kelm, P., Schmiedeke, S., Schockaert, S., Sikora, T., Trevisiol, M., Van Laere, O. (2015). Georeferencing Flickr Resources Based on Multimodal Features. In: Choi, J., Friedland, G. (eds) Multimodal Location Estimation of Videos and Images. Springer, Cham. https://doi.org/10.1007/978-3-319-09861-6_8

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