… Among many edge analytic applications, in this paper, we focus on delivering video analytics
at the edge. e ability to provide low latency video analytics is critical for applications in the …

… all video analytics deployments, we believe that in practice deployments will vary from
having all the analytics in the cloud (for small deployments of cameras), to all the analytics in pri…

… of interest in a live video feed using video analytics. The most important feature of the sensor
is that it follows the edge-computing paradigm, ie, the video analytics are run directly on the …

… data can also be offloaded to edge servers for processing. By leveraging the on-device …
federated video analytics system named FedVision to efficiently provision video analytics across …

… In [12], video quality and computing resources are selected to maximize successful queries;
… edge computing, eg, [36], [37], do not cater for video analytic metrics or the specifics of video …

… To this end, this study presents a Video Analytics Edge Computing (VAEC) system that
performs real-time enhanced situation awareness for person detection in a video surveillance …

… video is analyzed and which part of the workload could be offloaded to the edge, we dissect
the general video analytics … introduce video analytics for public safety and edge computing, …

… edge service framework for real-time video analytics applications — EdgeEye, which provides
a high-level abstraction of some important video … edge computing for live video analytics is …

… edge 7 servers are usually limited and highly dynamic, and then server 8 selection should be
adaptive in order to improve the performance 9 of video analytics… for video analytics, where …

… been developed to apply deep learning for video analytics. Although these advanced deep
… FastVA, which supports deep learning video analytics through edge processing and Neural …