Lexicon-based Browsers for Searching in News Video Archives

In this paper we present the methods and visualizations used in the 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. The search system is evaluated within the TRECVID benchmark. 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.

• Type: Conference
• Year: 2006
• Where: ICPR
• Authors: Cees Snoek, Dennis Koelma, Giang P. Nguyen, Marcel Worring, Ork de Rooij
• Keywords: Computer Vision, ICPR 2006, Semantic Similarity Space, Semantic Thread Space, Visual Similarity Space