Mediamill: advanced browsing in news video archives

  • Authors:

  • Marcel Worring;Cees Snoek;Ork de Rooij;Giang Nguyen;Richard van Balen;Dennis Koelma

  • Affiliations:

  • Intelligent Systems Lab Amsterdam, University of Amsterdam, Amsterdam, SJ, The Netherlands;Intelligent Systems Lab Amsterdam, University of Amsterdam, Amsterdam, SJ, The Netherlands;Intelligent Systems Lab Amsterdam, University of Amsterdam, Amsterdam, SJ, The Netherlands;Intelligent Systems Lab Amsterdam, University of Amsterdam, Amsterdam, SJ, The Netherlands;Intelligent Systems Lab Amsterdam, University of Amsterdam, Amsterdam, SJ, The Netherlands;Intelligent Systems Lab Amsterdam, University of Amsterdam, Amsterdam, SJ, The Netherlands

  • Venue:
  • CIVR'06 Proceedings of the 5th international conference on Image and Video Retrieval
  • Year:
  • 2006

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Abstract

In this paper we present our Mediamill video search engine. The basis for the engine is a semantic indexing process which derives a lexicon of 101 concepts. To support the user in navigating the collection, the system defines a visual similarity space, a semantic similarity space, a semantic thread space, and browsers to explore them. It extends upon [1] with improved browsing tools. The search system is evaluated within the TRECVID benchmark [2]. We obtain a top-3 result for 19 out of 24 search topics. In addition, we obtain the highest mean average precision of all search participants.