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

47 Citations (Scopus)
66 Downloads (Pure)

Abstract

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
PublisherIEEE Computer Society
Pages817-820
Number of pages4
ISBN (Print)0-7803-7304-9
DOIs
Publication statusPublished - Aug 2002

Publication series

Name
PublisherIEEE Press
Volume1

Keywords

  • DB-MMR: MULTIMEDIA RETRIEVAL
  • EWI-7305
  • IR-38263
  • METIS-209545

Cite this

Petkovic, M., Mihajlovic, V., Jonker, W., & Djordjevic-Kajan, S. (2002). Multi-Modal Extraction of Highlights from TV Formula 1 Programs. In S. Voloshynovskijy, T. Pun, & B. Macq (Eds.), Proceedings of the IEEE International Conference on Multimedia and Expo (ICME 2002) (pp. 817-820). Los Alamitos: IEEE Computer Society. https://doi.org/10.1109/ICME.2002.1035907