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Mediamill: Advanced Browsing in News Video Archives

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Image and Video Retrieval (CIVR 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4071))

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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.

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References

  1. Snoek, C., Worring, M., van Gemert, J., Geusebroek, J., Koelma, D., Nguyen, G., de Rooij, O., Seinstra, F.: Mediamill: Exploring news video archives based on learned semantics. In: ACM Multimedia, Singapore (2005)

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© 2006 Springer-Verlag Berlin Heidelberg

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Worring, M., Snoek, C., de Rooij, O., Nguyen, G., van Balen, R., Koelma, D. (2006). Mediamill: Advanced Browsing in News Video Archives. In: Sundaram, H., Naphade, M., Smith, J.R., Rui, Y. (eds) Image and Video Retrieval. CIVR 2006. Lecture Notes in Computer Science, vol 4071. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11788034_62

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  • DOI: https://doi.org/10.1007/11788034_62

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-36018-6

  • Online ISBN: 978-3-540-36019-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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