Title :
Cluster-temporal browsing of large news video databases
Author :
Rautiainen, Mika ; Ojala, Timo ; Seppanen, T.
Author_Institution :
MediaTeam Oulu, Oulu Univ., Finland
Abstract :
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.
Keywords :
content-based retrieval; image retrieval; speech recognition; video databases; video signal processing; automatic speech recognition transcripts; browsing efficiency; cluster-temporal browsing; conceptual features; content similarities; interactive video retrieval systems; large news video databases; lexical features; temporal adjacency; visual features; Automatic speech recognition; Content based retrieval; Image retrieval; Indexing; Navigation; Performance evaluation; Prototypes; Spatial databases; System testing; Visual databases;
Conference_Titel :
Multimedia and Expo, 2004. ICME '04. 2004 IEEE International Conference on
Print_ISBN :
0-7803-8603-5
DOI :
10.1109/ICME.2004.1394309
