Edge video analytics (EVA) emerges as a promising paradigm to decentralize video
analytics tasks to the edge of the network and thus improve user experience by enabling …

The emerging Edge computing paradigm facilitates the deployment of distributed AI-
applications and hardware, capable of processing video data in real time. AI-assisted video …

With the proliferation of video content from surveillance cameras, social media, and live
streaming services, the need for efficient video analytics has grown immensely. In recent …

Preserving privacy in image and video data captured from public environments is essential
for any research group that leverages, publishes, or shares such data. Although there are …

Massive amounts of video data are ubiquitously generated in personal devices and
dedicated video recording facilities. Analyzing such data would be extremely beneficial in …

Real-time edge-cloud video analytics systems have been widely used to support such
applications as traffic counting, surveillance, autonomous driving, Metaverse, etc. In such a …

Video stream analytics (VSA) systems fuel many exciting applications that facilitate people's
lives, but also raise critical concerns about exposing too much individuals' privacy. To …

Analytics on video recorded by cameras in public areas have the potential to fuel many
exciting applications, but also pose the risk of intruding on individuals' privacy …

Large volumes of video data recorded by the increasing mobile devices and embedded
sensors can be leveraged to answer queries of our lives, physical world and our evolving …

Intelligent Video surveillance systems, leveraging edge computing, have become
increasingly prevalent in various facilities, providing advanced monitoring and management …