Please use this identifier to cite or link to this item:
|Scopus||Web of Science®||Altmetric|
|Title:||Estimating camera overlap in large and growing networks|
Van Den Hengel, A.
|Citation:||Proceedings of the Second ACM/IEEE International Conference on Distributed Smart Cameras, 2008. (ICDSC 2008): pp.1-10|
|Conference Name:||ACM/IEEE International Conference on Distributed Smart Cameras (2nd : 2008 : Stanford, CA.)|
|Henry Detmold, Anton van den Hengel, Anthony Dick, Alex Cichowski, Rhys Hill, Ekim Kocadag, Yuval Yarom, Katrina Falkner and David S. Munro|
|Abstract:||Large-scale intelligent video surveillance requires an accurate estimate of the relationships between the fields of view of the cameras in the network. The exclusion approach is the only method currently capable of performing online estimation of camera overlap for networks of more than 100 cameras, and implementations have demonstrated the capability to support networks of 1000 cameras. However, these implementations include a centralised processing component, with the practical result that the resources (in particular, memory) of the central processor limit the size of the network that can be supported. In this paper, we describe a new, partitioned, implementation of exclusion, suitable for deployment to a cluster of commodity servers. Results for this implementation demonstrate support for significantly larger camera networks than was previously feasible. Furthermore, the nature of the partitioning scheme enables incremental extension of system capacity through the addition of more servers, without interrupting the existing system. Finally, formulae for requirements of system memory and bandwidth resources, verified by experimental results, are derived to assist engineers seeking to implement the technique.|
|Appears in Collections:||Computer Science publications|
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.