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ABSTRACT
Querying live media streams is a challenging problem that is becoming an essential requirement in a growing number of applications. Research in multimedia information systems has addressed and made good progress in dealing with archived data. Meanwhile, research in stream databases has received significant attention for querying alphanumeric symbolic streams. The lack of a unifying data model capable of representing multimedia data and providing reasonable abstractions for querying live multimedia streams poses the challenge of how to make the best use of data in video and other sensor networks for various applications including video surveillance, live conferencing and Eventweb. This paper presents a system that enables direct capture of media streams from sensors and automatically generates meaningful feature streams that can be queried by a data stream processor. The system provides an effective combination of extensible digital processing techniques and general data stream management research.
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Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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CITED BY 4
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Michael S. Lew , Nicu Sebe , Chabane Djeraba , Ramesh Jain, Content-based multimedia information retrieval: State of the art and challenges, ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP), v.2 n.1, p.1-19, February 2006
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