The case for admission control of mobile cameras into the live video analytics pipeline

Francescomaria Faticanti, F. Bronzino, F. Pellegrini
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Abstract

In this paper we consider the problem of orchestrating video analytics applications over an edge computing infrastructure. Video analytics applications have been traditionally associated to the processing of video streams generated by fixed video cameras. Nowadays, however, the availability of mobile video cameras has become pervasive. We argue that to take advantage of the presence of mobile video cameras---and their informative content---it may be necessary to refactor the edge orchestration logic. We propose a new solution that splits the problem into two connected actions: 1) Placement of processing functions in the infrastructure and 2) Admission of most informative cameras based on their field of view. We hence describe a possible scheme for joint video stream admission and orchestration. Finally, preliminary numerical results are presented, demonstrating that separating the two logic components can improve coverage while reducing the cost of deployment.
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允许控制移动摄像机进入实时视频分析管道的案例
在本文中,我们考虑了在边缘计算基础设施上编排视频分析应用程序的问题。传统上,视频分析应用程序与固定摄像机生成的视频流处理有关。然而,如今,移动摄像机的可用性已经变得普遍。我们认为,为了利用移动摄像机的存在——以及它们的信息内容——可能有必要重构边缘编排逻辑。我们提出了一个新的解决方案,将问题分为两个相互关联的行动:1)在基础设施中放置处理功能,2)根据其视野接纳最具信息量的相机。因此,我们描述了一种联合视频流接收和编排的可能方案。最后,给出了初步的数值结果,表明分离两个逻辑组件可以提高覆盖率,同时降低部署成本。
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The case for admission control of mobile cameras into the live video analytics pipeline Towards memory-efficient inference in edge video analytics Cost effective processing of detection-driven video analytics at the edge Decentralized modular architecture for live video analytics at the edge Auto-SDA: Automated video-based social distancing analyzer
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