Object Motion Detection Methods for Real-Time Video Surveillance: A Survey with Empirical Evaluation

Abstract

Automated moving object detection and analysis assumes a great significance in video surveillance. This article presents a comprehensive survey on the techniques of object-in-motion detection for video surveillance. In this paper, eight methods of object detection in video streams are implemented and evaluated empirically on five quality parameters for identifying the efficiency and effectiveness of these methods. For objective assessments of these methods, a standard dataset “CDnet2012” is used which consists of six different rigorous scenarios. In conclusion, an attempt has been made to identify the best method for different scenarios, employable in real-time video surveillance.