Improved adaptivity and robustness in decentralised multi-camera networks

Lukas Esterle*, Bernhard Rinner, Peter R. Lewis, Xin Yao

*Corresponding author for this work

Research output: Chapter in Book/Published conference outputConference publication


In this paper we present increased adaptivity and robustness in distributed object tracking by multi-camera networks using a socio-economic mechanism for learning the vision graph. To build-up the vision graph autonomously within a distributed smart-camera network, we use an ant-colony inspired mechanism, which exchanges responsibility for tracking objects using Vickrey auctions. Employing the learnt vision graph allows the system to optimise its communication continuously. Since distributed smart camera networks are prone to uncertainties in individual cameras, such as failures or changes in extrinsic parameters, the vision graph should be sufficiently robust and adaptable during runtime to enable seamless tracking and optimised communication. To better reflect real smart-camera platforms and networks, we consider that communication and handover are not instantaneous, and that cameras may be added, removed or their properties changed during runtime. Using our dynamic socio-economic approach, the network is able to continue tracking objects well, despite all these uncertainties, and in some cases even with improved performance. This demonstrates the adaptivity and robustness of our approach.

Original languageEnglish
Title of host publication2012 6th International Conference on Distributed Smart Cameras, ICDSC 2012
Number of pages6
ISBN (Print)978-1-4503-1772-6
Publication statusPublished - 2012
Event6th International Conference on Distributed Smart Cameras - Hong Kong, China
Duration: 30 Oct 20122 Nov 2012


Conference6th International Conference on Distributed Smart Cameras
Abbreviated titleICDSC 2012
CityHong Kong

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