Abstract
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.
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Yang, J., Hauptmann, A.G. (2006). Annotating News Video with Locations. In: Sundaram, H., Naphade, M., Smith, J.R., Rui, Y. (eds) Image and Video Retrieval. CIVR 2006. Lecture Notes in Computer Science, vol 4071. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11788034_16
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DOI: https://doi.org/10.1007/11788034_16
Publisher Name: Springer, Berlin, Heidelberg
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