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_toolkit1. The package has been developed for ROS Indigo in C++11 and Python, and tested on PCs equipped with Ubuntu 14.04 64bit.

A Distributed Calibration Algorithm for Color and Range Camera Networks

BASSO, FILIPPO;LEVORATO, RICCARDO;MUNARO, MATTEO;MENEGATTI, EMANUELE
2016

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_toolkit1. The package has been developed for ROS Indigo in C++11 and Python, and tested on PCs equipped with Ubuntu 14.04 64bit.
2016
Robot Operating System - Studies in Systems, Decision and Control
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3168752
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