Multi-Modal Extraction of Highlights from TV Formula 1 Programs

M. Petkovic, V. Mihajlovic, Willem Jonker, S. Djordjevic-Kajan

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

50 Citations (Scopus)
164 Downloads (Pure)


As amounts of publicly available video data grow, the need to automatically infer semantics from raw video data becomes significant. In this paper, we focus on the use of dynamic Bayesian networks (DBN) for that purpose, and demonstrate how they can be effectively applied for fusing the evidence obtained from different media information sources. The approach is validated in the particular domain of Formula I race videos. For that specific domain we introduce a robust audiovisual feature extraction scheme and a text recognition and detection method. Based on numerous experiments performed with DBN, we give some recommendations with respect to the modeling of temporal and atemporal dependences within the network. Finally, we present the experimental results for the detection of excited speech and the extraction of highlights, as well as the advantageous query capabilities of our system.
Original languageUndefined
Title of host publicationProceedings of the IEEE International Conference on Multimedia and Expo (ICME 2002)
EditorsS. Voloshynovskijy, T. Pun, B. Macq
Place of PublicationLos Alamitos
Number of pages4
ISBN (Print)0-7803-7304-9
Publication statusPublished - Aug 2002
EventIEEE International Conference on Multimedia and Expo, ICME 2002 - Lausanne, Switzerland
Duration: 26 Aug 200229 Aug 2002

Publication series

PublisherIEEE Press


ConferenceIEEE International Conference on Multimedia and Expo, ICME 2002
OtherAugust 26-29, 2002


  • EWI-7305
  • IR-38263
  • METIS-209545

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