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A Distributed Calibration Algorithm for Color and Range Camera Networks

  • Filippo BassoEmail author
  • Riccardo Levorato
  • Matteo Munaro
  • Emanuele Menegatti
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 625)

Abstract

In this tutorial chapter we present a package to calibrate multi-device vision systems such as camera networks or robots. The proposed approach is able to estimate—in a unique and consistent reference frame—the rigid displacements of all the sensors in a network of standard cameras, Kinect-like depth sensors and Time-of-Flight range sensors. The sensor poses can be estimated in a few minutes with a user-friendly procedure: the user is only asked to move a checkerboard around while the ROS nodes acquire the data and perform the calibration. To make the system scalable, the data analysis is distributed in the network. This results in a low bandwidth usage as well as a really fast calibration procedure. The ROS package is available on GitHub within the repository iaslab-unipd/calibration_toolkit (https://github.com/iaslab-unipd/calibration_toolkit). The package has been developed for ROS Indigo in C++11 and Python, and tested on PCs equipped with Ubuntu 14.04 64 bit.

Keywords

ROS Calibration Camera Depth Camera network Distributed system Kinect RGB-D 

Notes

Acknowledgments

The authors would like to thank Prof. Mohamed Chetouani, Salvatore Maria Anzalone and Stéphane Michelet from Université Pierre-et-Marie-Curie (UPMC) and the Institut des Systèmes Intelligents et de Robotique (ISIR) for their support and help.

The authors would also like to thank Jeff Burke, Alexander Horn and Randy Illum from University of California, Los Angeles (UCLA) for the extensive collaboration in designing and testing the calibration methods during the development of OpenPTrack [15]. OpenPTrack has been sponsored by UCLA REMAP and Open Perception. Key collaborators include the University of Padova and Electroland. Portions of the work have been supported by the National Science Foundation (IIS-1323767).

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Filippo Basso
    • 1
    Email author
  • Riccardo Levorato
    • 1
  • Matteo Munaro
    • 1
  • Emanuele Menegatti
    • 1
  1. 1.IAS-Lab, Department of Information Engineering (DEI)University of PadovaPadovaItaly

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