TY - GEN
T1 - A position free boresight calibration for INS-camera systems
AU - Bender, Daniel
AU - Cremers, Daniel
AU - Koch, Wolfgang
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/7/2
Y1 - 2016/7/2
N2 - In this paper, we present an innovative calibration procedure to determine the angle misalignments, also known as boresight, between the coordinate systems of an inertial navigation system (INS) and a camera. All currently known approaches integrate positional information from the INS in the optimization process. Thereby, the position errors in the range of a few meters of most INS devices negatively influence the accuracy of the boresight estimation in state-of-the-art calibration methods. By using line instead of classical point features within the calibration process, we are able to perform the optimization without positional information and avoid being affected by the corresponding noisy data. This can improve the calibration results for systems of all accuracy levels. For the first time, a reliable calibration for systems with poor positional estimations is possible. The presented approach can be applied to images observing a checkerboard, which allows the calibration of the intrinsic camera parameters and boresight misalignment angles from the same dataset. We confirm the high performance of the presented procedure by evaluating simulated and real-world experiments. The achieved results show the capability to reduce the boresight errors to small sub-degree values.
AB - In this paper, we present an innovative calibration procedure to determine the angle misalignments, also known as boresight, between the coordinate systems of an inertial navigation system (INS) and a camera. All currently known approaches integrate positional information from the INS in the optimization process. Thereby, the position errors in the range of a few meters of most INS devices negatively influence the accuracy of the boresight estimation in state-of-the-art calibration methods. By using line instead of classical point features within the calibration process, we are able to perform the optimization without positional information and avoid being affected by the corresponding noisy data. This can improve the calibration results for systems of all accuracy levels. For the first time, a reliable calibration for systems with poor positional estimations is possible. The presented approach can be applied to images observing a checkerboard, which allows the calibration of the intrinsic camera parameters and boresight misalignment angles from the same dataset. We confirm the high performance of the presented procedure by evaluating simulated and real-world experiments. The achieved results show the capability to reduce the boresight errors to small sub-degree values.
UR - http://www.scopus.com/inward/record.url?scp=85015155009&partnerID=8YFLogxK
U2 - 10.1109/MFI.2016.7849466
DO - 10.1109/MFI.2016.7849466
M3 - Conference contribution
AN - SCOPUS:85015155009
T3 - IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems
SP - 52
EP - 57
BT - 2016 IEEE lnternational Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE lnternational Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2016
Y2 - 19 September 2016 through 21 September 2016
ER -