An Architecture for a Task-Oriented Surveillance System: A Service- and Event-Based Approach

Due to the increasing threat posed by crime, industrial espionage and even terrorism, video surveillance systems have become more important and powerful during the last years. While most commercially available surveillance systems have to be managed by human operators, who constantly monitor all video streams, several experimental systems from different research groups already include robust video processing approaches for (semi-) automated surveillance. Still, most research activities focus on a sensororiented approach to video analytics of large and distributed camera networks, aiming to extract, analyze and store all extractable information from the video streams. In real-life applications, however, only a limited set of specific threats needs to be covered. Accordingly, only a small subset of potentially extractable information has to be monitored. Besides the huge amount of raw video data, modern surveillance systems are also extended with other sensors that deliver even more data. As a consequence, a new paradigm is introduced, called task-oriented information and data processing for surveillance systems. In the proposed system NEST (Network Enabled Surveillance and Tracking) following the task-oriented approach, every resource allocation, data acquisition, and analysis process is assigned to a specific surveillance task. In order to meet the requirements of taskoriented surveillance, the proposed architecture combines a Service-Oriented Architecture with an Event-Driven Architecture (Event-driven SOA).