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 …

Video analytics, loosely defined as autonomous understanding of events occurring in a
scene monitored by multiple video cameras, has been rapidly evolving in the last two …

Deep learning with Deep Neural Networks (DNNs) can achieve much higher accuracy on
many computer vision tasks than classic machine learning algorithms. Because of the high …

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 …

Video analytics with deep learning techniques has generated immense interest in academia
and industry, captivating minds with its transformative potential. Deep learning techniques …

Video analytics will drive a wide range of applications with great potential to impact society.
A geographically distributed architecture of public clouds and edges that extend down to the …

Abstract The NVIDIA AI City Challenge has been created to accelerate intelligent video
analysis that helps make cities smarter and safer. With millions of traffic video cameras …

This paper presents a novel dataset for traffic accidents analysis. Our goal is to resolve the
lack of public data for research about automatic spatio-temporal annotations for traffic safety …

Edge-cloud collaborative video analytics is transforming the way data is being handled,
processed, and transmitted from the ever-growing number of surveillance cameras around …

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 …