Many private and public organizations deploy large numbers of cameras, which are used in
application services for public safety, healthcare, and traffic control. Recent advances in …

Video cameras are becoming ubiquitous in our daily lives. With the recent advancement of
Artificial Intelligence (AI), live video analytics are enabling various useful services, including …

This paper demonstrates the effectiveness of our customized deep learning based video
analytics system in various applications focused on security, safety, customer analytics and …

Video cameras have been deployed at scale today. Driven by the breakthrough in deep
learning (DL), organizations that have deployed these cameras start to use DL-based …

As video camera deployments continue to grow, the need to process large volumes of real-
time data strains wide-area network infrastructure. When per-camera bandwidth is limited, it …

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 …

Owing to the massive amount of video data being generated as a result of high proliferation
of surveillance cameras, the manpower to monitor such system is relatively expensive …

In smart city scenarios, the huge proliferation of monitoring cameras scattered in public
spaces has posed many challenges to network and processing infrastructure. A few dozen …

Deep learning video analytic systems process live video feeds from multiple cameras with
computer vision models deployed on edge or cloud. To optimize utility for these systems …

Camera orientations (ie, rotation and zoom) govern the content that a camera captures in a
given scene, which in turn heavily influences the accuracy of live video analytics pipelines …