Automatic tagging and geotagging in video collections and communities

  • Authors:

  • Martha Larson;Mohammad Soleymani;Pavel Serdyukov;Stevan Rudinac;Christian Wartena;Vanessa Murdock;Gerald Friedland;Roeland Ordelman;Gareth J. F. Jones

  • Affiliations:

  • Delft University of Technology, Delft, the Netherlands;University of Geneva, Geneva, Switzerland;Yandex Moscow, Russia;Delft University of Technology;Novay, Enschede, Netherlands;Yahoo! Research Barcelona, Barcelona, Spain;International Computer Science Institute, Berkeley, CA;Netherlands Institute for Sound and Vision, and University of Twente;Dublin City University, Dublin, Ireland

  • Venue:
  • Proceedings of the 1st ACM International Conference on Multimedia Retrieval
  • Year:
  • 2011

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Abstract

Automatically generated tags and geotags hold great promise to improve access to video collections and online communities. We overview three tasks offered in the MediaEval 2010 benchmarking initiative, for each, describing its use scenario, definition and the data set released. For each task, a reference algorithm is presented that was used within MediaEval 2010 and comments are included on lessons learned. The Tagging Task, Professional involves automatically matching episodes in a collection of Dutch television with subject labels drawn from the keyword thesaurus used by the archive staff. The Tagging Task, Wild Wild Web involves automatically predicting the tags that are assigned by users to their online videos. Finally, the Placing Task requires automatically assigning geo-coordinates to videos. The specification of each task admits the use of the full range of available information including user-generated metadata, speech recognition transcripts, audio, and visual features.