Cameras are deployed at scale with the purpose of searching and tracking objects of
interest (eg, a suspected person) through the camera network on live videos. Such cross …

Today, video cameras are deployed in dense for monitoring physical places eg, city,
industrial, or agricultural sites. In the current systems, each camera node sends its feed to a …

Video cameras are pervasively deployed in city scale for public good or community safety (ie
traffic monitoring or suspected person tracking). However, analyzing large scale video feeds …

Camera deployments are ubiquitous, but existing methods to analyze video feeds do not
scale and are error-prone. We describe Optasia, a dataflow system that employs relational …

Organizations deploy a hierarchy of clusters-cameras, private clusters, public clouds-for
analyzing live video feeds from their cameras. Video analytics queries have many …

Driven by advances in computer vision and the falling costs of camera hardware,
organizations are deploying video cameras en masse for the spatial monitoring of their …

The world is witnessing an unprecedented increase in camera deployment. The USA and
UK, for instance, have one camera for every 8 people. Video analytics from these cameras …

With the installation of enormous public safety and transportation infrastructure cameras,
video analytics has come to play an essential part in public safety. Typically, video analytics …

Edge video analytics is becoming the solution to many safety and management tasks. Its
wide deployment, however, must first address the tension between inference accuracy and …

Video analytics pipelines have steadily shifted to edge deployments to reduce bandwidth
overheads and privacy violations, but in doing so, face an ever-growing resource tension …