Distributed One Dimensional Calibration and Localisation of a Camera Sensor Network

  • Brendan HalloranEmail author
  • Prashan Premaratne
  • Peter Vial
  • Inas Kadhim
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10362)


Metric calibration and localisation are crucial requirements for many higher-level robotic vision tasks, such as visual navigation and tracking. Furthermore, distributed algorithms are being increasingly used to create scalable camera sensor networks (CSN) which are resistant to node failure. We present a distributed algorithm for the calibration and localisation of a CSN. Our method involves a robust local calibration at each node using a 1D calibration object, consisting of collinear points moving about a single fixed point. Next, each node builds a vision graph and performs cluster-based bundle adjustment, utilising the structure of calibration object to produce pose estimates for its cluster. Finally, these estimates are brought to global consensus through Gaussian belief propagation. Experimental results validate our algorithm, showing that it has comparable performance to centralised algorithms, despite being distributed in nature.


Camera calibration Localisation Distributed algorithms Gaussian belief propagation 



This research has been conducted with the support of the Australian Government Research Training Program Scholarship.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Brendan Halloran
    • 1
    Email author
  • Prashan Premaratne
    • 1
  • Peter Vial
    • 1
  • Inas Kadhim
    • 1
  1. 1.University of WollongongWollongongAustralia

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