The MediaMill TRECVID 2004 Semantic Video Search Engine C. G. M. Snoek, M. Worring, J. M. Geusebroek, D. C. Koelma, F. J. Seinstra In TRECVID Workshop 2004. [bibtex] [pdf] [url]

This year the UvA-MediaMill team participated in the Feature Extraction and Search Task. We developed a generic approach for semantic concept classification using the semantic value chain. The semantic value chain extracts concepts from video documents based on three consecutive analysis links, named the content link, the style link, and the context link. Various experiments within the analysis links were performed, showing amongst others the merit of processing beyond key frames, the value of style elements, and the importance of learning semantic context. For all experiments a lexicon of 32 concepts was exploited, 10 of which are part of the Feature Extraction Task. Top three system-based ranking in 8 out of the 10 benchmark concepts indicates that our approach is very promising. Apart from this, the lexicon of 32 concepts proved very useful in an interactive search scenario with our semantic video search engine, where we obtained the highest mean average precision of all participants.

@InProceedings{SnoekPTRECVID2004,
  author       = "Snoek, C. G. M. and Worring, M. and Geusebroek, J. M. and Koelma, D. C.
                  and Seinstra, F. J.",
  title        = "The MediaMill TRECVID 2004 Semantic Video Search Engine",
  booktitle    = "TRECVID Workshop",
  year         = "2004",
  url          = "https://ivi.fnwi.uva.nl/isis/publications/2004/SnoekPTRECVID2004",
  pdf          = "https://ivi.fnwi.uva.nl/isis/publications/2004/SnoekPTRECVID2004/SnoekPTRECVID2004.pdf",
  has_image    = 1
}