Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/44236
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Type: | Conference paper |
Title: | Topology estimation for thousand-camera surveillance networks |
Author: | Detmold, H. Van Den Hengel, A. Dick, A. Cichowski, A. Hill, R. Kocadag, E. Falkner, K. Munro, D. |
Citation: | First ACM/IEEE International Conference on Distributed Smart Cameras, 25-28 September 2007:pp.195-202 |
Publisher: | IEEE |
Publisher Place: | CDROM |
Issue Date: | 2007 |
ISBN: | 1424413540 9781424413546 |
Conference Name: | ACM/IEEE International Conference on Distributed Smart Cameras (1st : 2007 : Vienna, Austria) |
Editor: | Rinner, B. Wolf, W. |
Abstract: | Surveillance camera technologies have reached the point whereby networks of a thousand cameras are not uncommon. Systems for collecting and storing the video generated by such networks have been deployed operationally, and sophisticated methods have been developed for interrogating individual video streams. The principal contribution of this paper is a scalable method for processing video streams collectively, rather than on a per camera basis, which enables a coordinated approach to large-scale video surveillance. To realise our ambition of thousand camera automated surveillance networks, we use distributed processing on a dedicated cluster. Our focus is on determining activity topology - the paths objects may take between cameras' fields of view. An accurate estimate of activity topology is critical to many surveillance functions, including tracking targets through the network, and may also provide a means for partitioning of distributed surveillance processing. We present several implementations using the exclusion algorithm to determine activity topology. Measurements reported for the key system component demonstrate scalability to networks with a thousand cameras. Whole-system measurements are reported for actual operation on over a hundred camera streams (this limit is based on the number of cameras and computers presently available to us, not scalability). Finally, we explore how to scale our approach to support multi-thousand camera networks. ©2007 IEEE. |
Description: | Copyright © 2007 IEEE |
DOI: | 10.1109/ICDSC.2007.4357524 |
Published version: | http://dx.doi.org/10.1109/icdsc.2007.4357524 |
Appears in Collections: | Aurora harvest Computer Science publications |
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hdl_44236.pdf | 917.68 kB | Author's post-print | View/Open |
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