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Hierarchical Modeling and Adaptive Clustering for Real-time Summarization of Compressed Rush Videos
| Content Provider | Semantic Scholar |
|---|---|
| Author | Ren, Jinchang Jiang, Jianmin Eckes, Christian |
| Copyright Year | 2009 |
| Abstract | In this paper, our techniques used in TRECVID’08 on BBC rush summarization are described. Firstly, rush videos are hierarchical modeled using formal language description. Then, shot detection and V-unit determination are applied for video structuring; junk frames within the model are also effectively removed. Thirdly, adaptive clustering is employed to group shots into clusters to remove retakes. Then, each selected shot is ranked according to its length and sum of activity level for summarization. Competitive results have proved the effectiveness and efficiency of our techniques fully implemented in compressed-domain. Our paper need not high-level semantics such as human object detection and audio signal analysis for summarization which provides a more flexible and general solution for this topic; |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://dmsri.inf.brad.ac.uk/publications/content/papers/RenJE2008-hierachical.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |