Multi-modal extraction of highlights from TV Formula 1 programs

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

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

48 Citations (Scopus)

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 languageEnglish
Title of host publicationProceedings 2002 IEEE International Conference on Multimedia and Expo (ICME'02)
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Pages817-820
Number of pages4
ISBN (Print)0-7803-7304-9
DOIs
Publication statusPublished - 2002
Externally publishedYes
Event2002 IEEE International Conference on Multimedia and Expo (ICME 2002) - Lausanne, Switzerland
Duration: 26 Aug 200229 Aug 2002

Conference

Conference2002 IEEE International Conference on Multimedia and Expo (ICME 2002)
Abbreviated titleICME 2002
CountrySwitzerland
CityLausanne
Period26/08/0229/08/02

Fingerprint Dive into the research topics of 'Multi-modal extraction of highlights from TV Formula 1 programs'. Together they form a unique fingerprint.

Cite this