Improved adaptivity and robustness in decentralised multi-camera networks


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.

Divisions: College of Engineering & Physical Sciences
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Event Title: 6th International Conference on Distributed Smart Cameras
Event Type: Other
Event Dates: 2012-10-30 - 2012-11-02
Uncontrolled Keywords: Electrical and Electronic Engineering,Electronic, Optical and Magnetic Materials
ISBN: 978-1-4503-1772-6
Last Modified: 26 Mar 2024 08:07
Date Deposited: 19 Jan 2015 14:40
Full Text Link: http://ieeexplo ... camera+networks
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Conference contribution
Published Date: 2012
Authors: Esterle, Lukas (ORCID Profile 0000-0002-0248-1552)
Rinner, Bernhard
Lewis, Peter R. (ORCID Profile 0000-0003-4271-8611)
Yao, Xin



Version: Accepted Version

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