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.File | Dimensione | Formato | |
---|---|---|---|
Basso_ROSChapter2015.pdf
accesso aperto
Tipologia:
Postprint (accepted version)
Licenza:
Accesso libero
Dimensione
2.78 MB
Formato
Adobe PDF
|
2.78 MB | Adobe PDF | Visualizza/Apri |
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.