Annotating News Video with Locations

  • Jun Yang
  • Alexander G. Hauptmann
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4071)


The location of video scenes is an important semantic descriptor especially for broadcast news video. In this paper, we propose a learning-based approach to annotate shots of news video with locations extracted from video transcript, based on features from multiple video modalities including syntactic structure of transcript sentences, speaker identity, temporal video structure, and so on. Machine learning algorithms are adopted to combine multi-modal features to solve two sub-problems: (1) whether the location of a video shot is mentioned in the transcript, and if so, (2) among many locations in the transcript, which are correct one(s) for this shot. Experiments on TRECVID dataset demonstrate that our approach achieves approximately 85% accuracy in correctly labeling the location of any shot in news video.


Support Vector Machine Noun Phrase True Location Candidate Location Parse Tree 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jun Yang
    • 1
  • Alexander G. Hauptmann
    • 1
  1. 1.School of Computer ScienceCarnegie Mellon UniversityPittsburghUSA

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