Extracting Objects and Events from MPEG Sequences for Video Highlights Indexing and Retrieval
- Main information
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Automatic recognition of highlights from videos is a fundamental and challenging problem for content-based indexing and retrieval applications. In this paper, we propose techniques to solve this problem using knowledge supported extraction of semantics, and employing compressed-domain processing for efficiency. Firstly, knowledge-supported rules are utilized for shot detection on the extracted DC-images, and statistical skin detection is applied for human object detection. Secondly, through filtering outliers in motion vectors, improved detection of camera motions like zooming, panning and tilting are achieved. High-level semantics like video highlights are then automatically extracted via low-level analysis in the detection of human objects and camera motion events, and finally these highlights are taken for shot-level annotation, indexing and retrieval. Results from large data of test videos have demonstrated the accuracy and robustness of the proposed techniques. No referenced Knowhow defined WP5: Detection, Extraction and Annotation of Knowledge. School of Informatics University of Bradford Jianmin Jiang, Jinchang Ren 2009-04-16 11:07 Request for more detail
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For LIVE project internal research purposes only. For LIVE project internal development purposes only.
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Copyright School of Informatics, University of Bradford. Patent Protection not sought. Licensing Protection not sought. Utility Model Protection not sought. To appear in Journall of Multimedia Closed, attachment is not public
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