… , a video analytics system that optimizes resource consumption and inference accuracy of
video analytics pipelines, by adapting their configurations in real-time. Using live video feeds …

… This section provides an overview of video analytics before delving into the key
challenges … Scaling real-time, wide-area video analytics poses a challenge for bandwidth-limited, …

… In this section, we add the workload adaptation techniques proposed in Distream onto
VideoEdge [19] to examine how Distream could enhance its performance. We select VideoEdge …

… , a video analytics system that processes thousands of video analytics queries on live video
streams … This is comparable to the scalability of schedulers in big data clusters, and video …

… is a crucial task for video analytics. Unlike existing adaptation approaches with fixed batch …
first time propose the batch adaptation for video streaming in video analytics applications. We …

… video analytics offloading configuration and bandwidth allocation scheme for a multi-user
edge-assisted video analytics … Satyanarayanan, “Scalable crowd-sourcing of video from mobile …

… limitations so that video analytics are scalable with more consistent … adaptation service. As
retraining an expert model takes significant compute resources and time (§1), the adaptation …

… video analytics in real-world scenarios and to bring more flexibility, agility, and efficiency to
the space. Ideally, a live video analytics … Chameleon: scalable adaptation of video analytics. …

… Therefore, we aim to design an efficient decoder to schedule the multiple pipelines for
video analytics … Scaling video analytics also attracts lots of attention from researchers, [68]…

… video analytics framework to process real-time video streams and also do batch video analytics…
of a distributed VAP, in terms of scalability, effectiveness and fault-tolerance, leaving data …