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Adaptive Metadata Management System for Distributed Video Content Analysis

机译:分布式视频内容分析的自适应元数据管理系统

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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.
机译:视频处理算法开发的科学进步现在允许各种基于分布式和协作式视觉的应用程序。然而,在这方面缺乏公认的标准驱使系统开发者构建特定的系统,从而防止例如。内容分析组件在不同环境中的升级或系统重用。结果,对用于存储和管理视频分析结果的通用,独立于上下文的自适应系统的需求显而易见。为了解决此问题,我们提出了由多代理系统支持的独立于数据模式的数据仓库。该系统依赖于语义Web知识表示格式,即RDF,以确保在模式转换和知识检索方面具有最大的适应性和灵活性。存储系统本身,即数据仓库,来自知识管理的最新技术,可在监视系统内提供有效的分析和报告功能。

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