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The paper describes cluster-temporal browsing of news video databases. Cluster-temporal browsing combines content similarities and temporal adjacency into a single representation. Visual, conceptual and lexical features are used to organize and view similar shot content. Interactive experiments with eight test users have been carried out using a database of roughly 60 hours of news video. Results indicate improvements in browsing efficiency when automatic speech recognition transcripts are incorporated into browsing by visual similarity. The cluster-temporal browsing application received positive comments from the test users and performed well in overall comparison with interactive video retrieval systems in TRECVID 2003 evaluation.
Rautiainen et al. (Mon,) studied this question.