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Extracting Semantics and Content Adaptive Summarisation for Effective Video Retrieval

Main information
In this paper, we provide a system for semantic video retrieval in which extracted semantic contents are used to generate summarised videos for effective delivery of retrieved results. Firstly, several useful features are extracted in compressed video on the basis of the DC-images and motion vectors. Secondly, shot changes are detected to enable shot-level content indexing and retrieval. Thirdly, several semantics concepts are automatically detected including outdoor/indoor scenes, building, sky and human objects. The results of detected shots and extracted semantic concepts are then used for semantic indexing of video contents. Furthermore, a combined measurement is produced from these semantics for content adaptive video summarisation. According to the network performance, the retrieved video can be delivered at various sizes using our summarisation techniques for efficiency.  
No referenced Knowhow defined
WP5: Detection, Extraction and Annotation of Knowledge. 
School of Informatics University of Bradford  Jianmin Jiang, Jinchang Ren 
2009-09-28 15:43  Request for more detail


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For LIVE project internal research purposes only.  For educational purposes only - if public document. 


Protection Status
Copyright School of Informatics, University of Bradford.  Add to LIVE's Intellectual Property Watch List 
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Published in EU NEM Summit 2009 
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