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Journal of Real-Time Image Processing

, Volume 12, Issue 4, pp 813–826 | Cite as

Efficient network clustering for traffic reduction in embedded smart camera networks

  • Ali Akbar Zarezadeh
  • Christophe BobdaEmail author
  • Franck Yonga
  • Michael Mefenza
Special Issue Paper

Abstract

In this work, a clustering approach for bandwidth reduction in distributed smart camera networks is presented. Properties of the environment such as camera positions and environment pathways, as well as dynamics and features of targets are used to limit the flood of messages in the network. To better understand the correlation between camera positioning and pathways in the scene on one hand and temporal and spatial properties of targets on the other hand, and to devise a sound messaging infrastructure, a unifying probabilistic modeling for object association across multiple cameras with disjointed view is used. Communication is efficiently handled using a task-oriented node clustering that partition the network in different groups according to the pathway among cameras, and the appearance and temporal behavior of targets. We propose a novel asynchronous event exchange strategy to handle sporadic messages generated by non-frequent tasks in a distributed tracking application. Using a Xilinx-FPGA with embedded Microblaze processor, we could show that, with limited resource and speed, the embedded processor was able to sustain a high communication load, while performing complex image processing computations.

Keywords

Smart camera networks \(\cdot\) Communication infrastructure \(\cdot\) Hardware/software system \(\cdot\) FPGA \(\cdot\) Embbeded middelware 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Ali Akbar Zarezadeh
    • 1
  • Christophe Bobda
    • 2
    Email author
  • Franck Yonga
    • 2
  • Michael Mefenza
    • 2
  1. 1.Dspace GmbHPaderbornGermany
  2. 2.CSCE DepartmentUniversity of ArkansasFayettevilleUSA

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