Exploring video content structure for hierarchical summarization

  title={Exploring video content structure for hierarchical summarization},
  author={Xingquan Zhu and Xindong Wu and Jianping Fan and Ahmed K. Elmagarmid and Walid G. Aref},
  journal={Multimedia Systems},
In this paper, we propose a hierarchical video summarization strategy that explores video content structure to provide the users with a scalable, multilevel video summary. First, video-shot- segmentation and keyframe-extraction algorithms are applied to parse video sequences into physical shots and discrete keyframes. Next, an affinity (self-correlation) matrix is constructed to merge visually similar shots into clusters (supergroups). Since video shots with high similarities do not necessarily… CONTINUE READING
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Clustering algorithms. In: Frakes W, Bazea-Yates R (eds) Information retrieval: data structure and algorithm

  • E Rasmussen
  • 1992
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