Combining multi-resolution evidence for georeferencing Flickr images

  • Authors:
  • Olivier Van Laere;Steven Schockaert;Bart Dhoedt

  • Affiliations:
  • Department of Information Technology, Ghent University, IBBT, Belgium;Dept. of Applied Mathematics and Computer Science, Ghent University, Belgium;Department of Information Technology, Ghent University, IBBT, Belgium

  • Venue:
  • SUM'10 Proceedings of the 4th international conference on Scalable uncertainty management
  • Year:
  • 2010

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Abstract

We explore the task of determining the geographic location of photos on Flickr, using combined evidence from Naive Bayes classifiers that are trained at different spatial resolutions. In particular, we estimate the location of Flickr photos, based on their tags, at four different scales, ranging from a city-level granularity to fine-grained intracity areas. Using Dempster-Shafer's evidence theory, we combine the output of the different classifiers into a single mass assignment. We demonstrate experimentally that the induced belief and plausibility measures are useful to determine whether there is sufficient evidence to classify the photo at a given granularity. Thus an adaptive method is obtained, by which photos are georeferenced at the most appropriate resolution.