Intelligent Video Surveillance System Using Faster Regional Convolutional Neural Networks

Abstract

Over the years, the need for intelligent video surveillance has increased in other to enhance security and safety in the society. Government, private organization and individual need to make sure its properties are kept safe from intruders and as such intelligent video surveillance plays a key role in ensuring that this is achieved. Intelligent video surveillance is embedded with the capability of providing real time intelligent surveillance and also automatically provide analysis of video and image data without human operation. In the development of such systems, computer vision, machine learning and deep learning plays a vital role in achieving this. Therefore, this paper provides a general survey on intelligent video surveillance system, overview of background concept and discussion on object detections and classification, tracking and deep networks. Also, this paper presents an efficient and faster object detection and classification techniques for intelligent video surveillance.