Multi-Stage Video Analysis Framework

Video monitoring systems are a necessity in the modern times. Although some people object the idea of ‘being watched’, surveillance systems actually improve the level of public security, allowing the system operators to detect threats and the security forces to react in time. Surveillance systems evolved in the recent years from simple CCTV systems into complex structures, containing numerous cameras and advanced monitoring centers, equipped with sophisticated hardware and software. However, the future of surveillance systems belongs to automatic tools that assist the system operator and notice him on the detected security threats. This is important, because in complex systems consisting of tens or hundreds of cameras, the operator is not able to notice all the events. In the last few years many publications regarding automatic video content analysis have been presented. However, these systems are usually focused on a single type of human or vehicle activity. No complex approach to the problem of automatic video surveillance system has been proposed so far. In order to address this problem, the authors designed a framework that analyses camera images on multiple levels, from basic detection of moving objects to advanced object recognition and automatic detection of important events. The proposed system has a flexible structure, with functional modules that may be selected so that the system suits the need of a particular application. These modules are based on algorithms proposed by various authors, adapted to the needs of the presented framework and enhanced by the authors in order to provide an efficient solution for automatic detection of important security threats in video monitoring systems. The chapter is organized as follows. Section 2 presents the general structure of the proposed framework and a method of data exchange between system elements. Section 3 is describing the low-level analysis modules for detection and tracking of moving objects. In Section 4 we present the object classification module. Sections 5 and 6 describe specialized modules for detection and recognition of faces and license plates, respectively. In section 7 we discuss how video analysis results provided by other modules may be used for automatic detection of events related to possible security threats. The chapter ends with conclusions and discussion of future framework development.