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 …

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 …

UTOMATED video surveillance addresses real-time observation of people and vehicles
within a busy environment, leading to a description of their actions and interactions. The …

Video analytics technology has matured and found application in a variety of fields over the
past decade. This chapter discusses the current state-ofthe-art, and describes challenges for …

The topic of computer vision has emerged as one that is fast developing, altering how we
examine and comprehend pictures and movies. Image and video analysis has significantly …

Urban environments present unique challenges from the perspective of surveillance and
security. High volumes of activity data, different weather conditions, crowded scenes …

From the streets of London to subway stations in New York City, hundreds of thousands of
surveillance cameras ubiquitously collect hundreds of thousands of videos, often running …

Many mobile applications have been developed to apply deep learning for video analytics.
Although these advanced deep learning models can provide us with better results, they also …

Over the past 10 years, computer vision research has matured significantly. Although some
of the core problems, such as object recognition and shape estimation are far from solved …

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 …