Abstract
Scientific advances in the development of video processing algorithms now allow various distributed and collaborative vision-based applications. However, the lack of recognised standard in this area drives system developers to build specific systems, preventing from e.g. content analysis components upgrade or system reuse in different environments. As a result, the need for a generic, context-independent and adaptive system for storing and managing video analysis results comes out as conspicuous. In order to address this issue, we propose a data schema-independent data warehouse backed by a multiagent system. This system relies on the semantic web knowledge representation format, namely the RDF, to guarantee maximum adaptability and flexibility regarding schema transformation and knowledge retrieval. The storage system itself, namely data warehouse, comes from the state-of-the-art technologies of knowledge management, providing efficient analysis and reporting capabilities within the monitoring system.
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Carincotte, C., Desurmont, X., Bastide, A. (2008). Adaptive Metadata Management System for Distributed Video Content Analysis. In: Blanc-Talon, J., Bourennane, S., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2008. Lecture Notes in Computer Science, vol 5259. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88458-3_30
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DOI: https://doi.org/10.1007/978-3-540-88458-3_30
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