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Solution space exploration of volumetric surveillance using a general taxonomy

机译:使用一般分类法进行体积监测的解决方案空间探索

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Visual surveillance systems provide real time monitoring of the events or the environment. The availability of low cost sensors and processors has increased the number of possible applications of these kinds of systems. However, designing an optimized visual surveillance system for a given application is a challenging task, which often becomes a unique design task for each system. Moreover, the choice of components for a given surveillance application out of a wide spectrum of available alternatives is not an easy job. In this paper, we propose to use a general surveillance taxonomy as a base to structure the analysis and development of surveillance systems. We demonstrate the proposed taxonomy for designing a volumetric surveillance system for monitoring the movement of eagles in wind parks aiming to avoid their collision with wind mills. The analysis of the problem is performed based on taxonomy and behavioral and implementation models are identified to formulate the solution space for the problem. Moreover, we show that there is a need for generalized volumetric optimization methods for camera deployment.
机译:视觉监视系统提供对事件或环境的实时监视。低成本传感器和处理器的可用性增加了这类系统的可能应用数量。但是,为给定的应用程序设计优化的视觉监视系统是一项艰巨的任务,对于每个系统,这通常成为唯一的设计任务。此外,要从各种可用替代方案中为给定的监视应用程序选择组件并非易事。在本文中,我们建议以通用监视分类法为基础来构建监视系统的分析和开发。我们演示了拟议的分类法,用于设计用于监视风电场中鹰的运动的体积监视系统,以防止它们与风车碰撞。根据分类法和行为进行问题分析,并确定实现模型以制定问题的解决方案空间。此外,我们表明需要用于摄像机部署的通用体积优化方法。

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