Ubuntu 14.04+ROS indigo: Ubuntu 16.04+ROS kinetic:
Kalibr is a toolbox that solves the following calibration problems:
- Multiple camera calibration: intrinsic and extrinsic calibration of a camera-systems with non-globally shared overlapping fields of view
- Visual-inertial calibration calibration (camera-IMU): spatial and temporal calibration of an IMU w.r.t a camera-system
- Rolling Shutter Camera calibration: full intrinsic calibration (projection, distortion and shutter parameters) of rolling shutter cameras
Please find more information on the wiki pages of this repository.
For questions or comments, please open an issue on Github.
A video tutorial for the IMU-camera calibration can be found here:
(Credits: @indigomega)
- Paul Furgale
- Hannes Sommer
- Jérôme Maye
- Jörn Rehder
- Thomas Schneider (email)
- Luc Oth
The calibration approaches used in Kalibr are based on the following papers. Please cite the appropriate papers when using this toolbox or parts of it in an academic publication.
- Joern Rehder, Janosch Nikolic, Thomas Schneider, Timo Hinzmann, Roland Siegwart (2016). Extending kalibr: Calibrating the extrinsics of multiple IMUs and of individual axes. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pp. 4304-4311, Stockholm, Sweden.
- Paul Furgale, Joern Rehder, Roland Siegwart (2013). Unified Temporal and Spatial Calibration for Multi-Sensor Systems. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Tokyo, Japan.
- Paul Furgale, T D Barfoot, G Sibley (2012). Continuous-Time Batch Estimation Using Temporal Basis Functions. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pp. 2088–2095, St. Paul, MN.
- J. Maye, P. Furgale, R. Siegwart (2013). Self-supervised Calibration for Robotic Systems, In Proc. of the IEEE Intelligent Vehicles Symposium (IVS)
- L. Oth, P. Furgale, L. Kneip, R. Siegwart (2013). Rolling Shutter Camera Calibration, In Proc. of the IEEE Computer Vision and Pattern Recognition (CVPR)
This work is supported in part by the European Union's Seventh Framework Programme (FP7/2007-2013) under grants #269916 (V-Charge), and #610603 (EUROPA2).
Copyright (c) 2014, Paul Furgale, Jérôme Maye and Jörn Rehder, Autonomous Systems Lab, ETH Zurich, Switzerland
Copyright (c) 2014, Thomas Schneider, Skybotix AG, Switzerland
All rights reserved.
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
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Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
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Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
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