CamSim: A distributed smart camera network simulator

Lukas ESTERLE, Peter R. LEWIS, Horatio CAINE, Xin YAO, Bernhard RINNER

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

15 Citations (Scopus)

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. © 2013 IEEE.
Original languageEnglish
Title of host publicationProceedings - IEEE 7th International Conference on Self-Adaptation and Self-Organizing Systems Workshops, SASOW 2013
PublisherIEEE Computer Society
Pages19-20
Number of pages2
ISBN (Print)9781479950867
DOIs
Publication statusPublished - Sept 2013
Externally publishedYes

Keywords

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

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