Geo-Location Estimation of Flickr Images: Social Web Based Enrichment

  • Claudia Hauff
  • Geert-Jan Houben
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7224)


Estimating the geographic location of images is a task which has received a lot of attention in recent years. Large numbers of items uploaded to Flickr do not contain GPS-based latitude/longitude coordinates, although it would be beneficial to obtain such geographic information for a wide variety of potential applications such as travelogues and visual place descriptions. While most works in this area consider an image’s textual meta-data to estimate its geo-location, we consider an additional textual dimension: the image owner’s traces on the social Web, in particular on the micro-blogging platform Twitter. We investigate the following question: does enriching an image’s available textual meta-data with a user’s tweets improve the accuracy of the geographic location estimation process? The results show that this is indeed the case; in an oracle setting, the median error in kilometres decreases by 87%, in the best automatic approach the median error decreases by 56%.


Language Model Median Error Training Corpus Geographic Spread Training Item 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Claudia Hauff
    • 1
  • Geert-Jan Houben
    • 1
  1. 1.WISDelft University of TechnologyDelftThe Netherlands

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