Based on a simple temporal structural model of a news program, the paper presents a practical solution to automatic news story segmentation by integrating syntactic and semantic methods. First, a syntactic segmentation method is used to detect the shot boundaries in order to partition video frames into video shots. Then, a semantic segmentation method based on graph-theoretical cluster analysis is developed to classify the video shots into anchorperson shots and news footage shots. Finally, a structural model of news video is used to complete the news-story segmentation. The proposed method obtains a precision of 90.45% and a recall of 95.83% in the segmentation experiment of 168 news stories from two Hong Kong news stations.
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Gao et al. (2002) studied this question.
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