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Pinar Duygulu, Jia-Yu Pan, and David A. Forsyth. Towards Auto-Documentary: Tracking the Evolution of News Stories. In Proceedings
of the ACM Multimedia Conference, 2004.
New York, NY, October 10-16, 2004
News videos constitute an important source of information for tracking and documenting important events. In these videos, news stories are often accompanied by short video shots that tend to be repeated during the course of the event. Automatic detection of such repetitions is essential for creating auto-documentaries, for alleviating the limitation of traditional textual topic detection methods. In this paper, we propose novel methods for detecting and tracking the evolution of news over time. The proposed method exploits both visual cues and textual information to summarize evolving news stories. Experiments are carried on the TREC-VID data set consisting of 120 hours of news videos from two different channels.
@InProceedings{MM04AutoDocumentary,
author = {Pinar Duygulu and Jia-Yu Pan and David A. Forsyth},
title = {Towards Auto-Documentary: Tracking the Evolution of News Stories},
booktitle = {Proceedings of the ACM Multimedia Conference},
year = 2004,
wwwnote = {New York, NY, October 10-16, 2004},
abstract = {News videos constitute an important source of information for tracking and documenting important events. In these videos, news stories are often accompanied by short video shots that tend to be repeated during the course of the event. Automatic detection of such repetitions is essential for creating auto-documentaries, for alleviating the limitation of traditional textual topic detection methods. In this paper, we propose novel methods for detecting and tracking the evolution of news over time. The proposed method exploits both visual cues and textual information to summarize evolving news stories. Experiments are carried on the TREC-VID data set consisting of 120 hours of news videos from two different channels.},
bib2html_pubtype = {Refereed Conference},
bib2html_rescat = {Multimedia Data Mining},
}
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