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This paper presents a novel framework designed for calculating the topology of overlapping cameras in large surveillance systems. Such a framework is a key enabler for efficient network-wide surveillance, e.g. inter-camera tracking, especially in large surveillance networks. The framework presented can be adapted to utilise numerous contradiction and correlation approaches to identify overlapping portions of camera views using activity within the system. It can also utilise a various arbitrary occupancy cells which can be used to adjust both the memory requirements and accuracy of the topology generated. The framework is evaluated for its memory usage, processing speed and the accuracy of its overlap topology on a 26 camera dataset using various approaches. A further examination of memory requirements and processing speed on a larger 200 camera network is also presented. The results demonstrate that the framework significantly reduces memory requirements and improves execution speed whilst producing useful topologies from a large surveillance system at real-time speeds.