A Survey of Automatic Event Detection in Multi-Camera Third Generation Surveillance Systems

Abstract

Third generation surveillance systems are largely requested for intelligent surveillance of different scenarios such as public areas, urban traffic control, smart homes and so on. They are based on multiple cameras and processing modules that integrate data coming from a large surveillance space. The semantic interpretation of data from a multi-view context is a challenging task and requires the development of image processing methodologies that could support applications in extensive and real-time contexts. This paper presents a survey of automatic event detection functionalities that have been developed for third generation surveillance systems with a particular emphasis on open problems that limit the application of computer vision methodologies to commercial multi-camera systems.