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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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
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