Middleware for video surveillance networks
Proceedings of the international workshop on Middleware for sensor networks
Searching in space and time: a system for forensic analysis of large video repositories
Proceedings of the 1st international conference on Forensic applications and techniques in telecommunications, information, and multimedia and workshop
Contradiction and Correlation for Camera Overlap Estimation
AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
Finding camera overlap in large surveillance networks
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
Time-Delayed Correlation Analysis for Multi-Camera Activity Understanding
International Journal of Computer Vision
A distributed topological camera network representation for tracking applications
IEEE Transactions on Image Processing - Special section on distributed camera networks: sensing, processing, communication, and implementation
Modeling Coverage in Camera Networks: A Survey
International Journal of Computer Vision
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Estimating the paths that moving objects can take through the fields of view of possibly non-overlapping cameras, also known as their activity topology, is an important step in the effective interpretation of surveillance video. Existing approaches to this problem involve tracking moving objects within cameras, and then attempting to link tracks across views. In contrast we propose an approach which begins by assuming all camera views are potentially linked, and successively eliminates camera topologies that are contradicted by observed motion. Over time, the true patterns of motion emerge as those which are not contradicted by the evidence. These patterns may then be used to initialise a finer level search using other approaches if required. This method thus represents an efficient and effective way to learn activity topology for a large network of cameras, particularly with a limited amount of data.