Intelligent Urban Video Surveillance System for Automatic Vehicle Detection and Tracking in Clouds

Nowadays, digital surveillance systems are ubiquitously installed and continuously generate huge amount of video data. Very often, human inspection of the recorded videois still required for threat detection. Even though automated techniques exist to facilitate the detection of potential security problems, it remains a highly computation demanding task to process these data. The emergence of cloud environments has made feasible to deploy intelligent video surveillance technologies as services through Internet to enhance public security. In this paper, we present a novel system aiming at bringing together automatic license plate recognition engines and cloud computing technology in order to realize massive data analysis and enable the detection and tracking of a target vehicle in a city with a given license plate number. It realizes a fully integrated system with a surveillance network of city scale, automatic large scale data retrieval and analysis, combination with pattern recognition technology to achieve contextual information analysis. Performance evaluation and some results of applying the proposed system to real-world data are demonstrated and the experiences we gained when implementing it are also discussed.