CamSim: a distributed smart camera network simulator

Lukas Esterle, Peter R. Lewis, Horatio Caine, Xin Yao, Bernhard Rinner

Research output: Chapter in Book/Published conference outputConference publication

Abstract

Smart cameras allow pre-processing of video data on the camera instead of sending it to a remote server for further analysis. Having a network of smart cameras allows various vision tasks to be processed in a distributed fashion. While cameras may have different tasks, we concentrate on distributed tracking in smart camera networks. This application introduces various highly interesting problems. Firstly, how can conflicting goals be satisfied such as cameras in the network try to track objects while also trying to keep communication overhead low? Secondly, how can cameras in the network self adapt in response to the behavior of objects and changes in scenarios, to ensure continued efficient performance? Thirdly, how can cameras organise themselves to improve the overall network's performance and efficiency? This paper presents a simulation environment, called CamSim, allowing distributed self-adaptation and self-organisation algorithms to be tested, without setting up a physical smart camera network. The simulation tool is written in Java and hence allows high portability between different operating systems. Relaxing various problems of computer vision and network communication enables a focus on implementing and testing new self-adaptation and self-organisation algorithms for cameras to use.

Original languageEnglish
Title of host publicationProceedings : IEEE 7th international conference on Self-Adaptation and Self-Organizing Systems Workshops
Subtitle of host publicationSASOW 2013
PublisherIEEE
Pages19-20
Number of pages2
ISBN (Print)978-1-4799-5086-7
DOIs
Publication statusPublished - 2014
Event7th international conference on Self-Adaptation and Self-Organizing Systems Workshops - Philadelphia, PA, United States
Duration: 9 Sept 201313 Sept 2013

Workshop

Workshop7th international conference on Self-Adaptation and Self-Organizing Systems Workshops
Abbreviated titleSASOW 2013
Country/TerritoryUnited States
CityPhiladelphia, PA
Period9/09/1313/09/13

Bibliographical note

© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Keywords

  • computer vision
  • distributed smart cameras
  • self-adaptation
  • self-organisation
  • simulation
  • software

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  • A modelling and simulation environment for self-aware and self-expressive systems

    Nya, T. D., Stilkerich, S. C. & Lewis, P. R., 2014, Proceedings : IEEE 7th international conference on Self-Adaptation and Self-Organizing Systems Workshops: SASOW 2013. IEEE, p. 65-70 6 p.

    Research output: Chapter in Book/Published conference outputConference publication

    Open Access
    File
  • Distributed sequential task allocation in foraging swarms

    Goldingay, H. & van Mourik, J., 11 Sept 2013, SASO: 2013 IEEE 7th international conference on Self-Adaptive and Self-Organizing Systems. IEEE, p. 149-158 10 p.

    Research output: Chapter in Book/Published conference outputConference publication

    Open Access
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  • Learning to be different: heterogeneity and efficiency in distributed smart camera networks

    Lewis, P. R., Esterle, L., Chandra, A., Rinner, B. & Yao, X., 2013, SASO: 2013 IEEE 7th international conference on Self-Adaptive and Self-Organizing Systems. IEEE, p. 209-218 10 p.

    Research output: Chapter in Book/Published conference outputConference publication

    Open Access
    File

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