The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Automatic camera and range sensor calibration using a single shot
Abstract
As a core robotic and vision problem, camera and range sensor calibration have been researched intensely over the last decades. However, robotic research efforts still often get heavily delayed by the requirement of setting up a calibrated system consisting of multiple cameras and range measurement units. With regard to removing this burden, we present a toolbox with web interface for fully automatic camera-to-camera and camera-to-range calibration. Our system is easy to setup and recovers intrinsic and extrinsic camera parameters as well as the transformation between cameras and range sensors within one minute. In contrast to existing calibration approaches, which often require user intervention, the proposed method is robust to varying imaging conditions, fully automatic, and easy to use since a single image and range scan proves sufficient for most calibration scenarios. Experimentally, we demonstrate that the proposed checkerboard corner detector significantly outperforms current state-of-the-art. Furthermore, the proposed camera-to-range registration method is able to discover multiple solutions in the case of ambiguities. Experiments using a variety of sensors such as grayscale and color cameras, the Kinect 3D sensor and the Velodyne HDL-64 laser scanner show the robustness of our method in different indoor and outdoor settings and under various lighting conditions.
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Cites
Distinctive Image Features from Scale-Invariant Keypoints
Lowe, D. G. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000029664.99615.94 · Cited by 55,589
SURF: Speeded Up Robust Features
Bay, H., Tuytelaars, T., & Van Gool, L. (2006) · Lecture Notes in Computer Science · doi:10.1007/11744023_32 · Cited by 14,955
A Combined Corner and Edge Detector
Harris, C., & Stephens, M. (1988) · Procedings of the Alvey Vision Conference 1988 · doi:10.5244/c.2.23 · Cited by 12,901
Shi, J., & Tomasi (1994) · Proceedings of IEEE Conference on Computer Vision and Pattern Recognition CVPR-94 · doi:10.1109/cvpr.1994.323794 · Cited by 7,724 · cited 2×
“We compare our approach to several competitive baseline methods: Harris corners [8] using the Shi-Tomasi criterium [17], a reimplementation of the method of Ha et al.”
BackgroundMethod
Cited by
Are we ready for autonomous driving? The KITTI vision benchmark suite
Geiger, A., Lenz, P., & Urtasun, R. (2012) · 2012 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2012.6248074 · Cited by 14,897
Self-citationVision meets robotics: The KITTI dataset
Geiger, A., Lenz, P., Stiller, C., & Urtasun, R. (2013) · The International Journal of Robotics Research · doi:10.1177/0278364913491297 · Cited by 9,913
Self-citationA new performance measure and evaluation benchmark for road detection algorithms
Fritsch, J., Kuhnl, T., & Geiger, A. (2013) · 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013) · doi:10.1109/itsc.2013.6728473 · Cited by 690
Self-citationKAIST Multi-Spectral Day/Night Data Set for Autonomous and Assisted Driving
Choi, Y., Kim, N., Hwang, S., Park, K., Yoon, J. S., An, K., & Kweon, I. S. (2018) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2018.2791533 · Cited by 370
Limo: Lidar-monocular visual odometry
Graeter, J., Wilczynski, A., & Lauer, M. (2018) · 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2018.8594394 · Cited by 261
Metadata
- Authors
- Geiger, A., Moosmann, F., Car, O., & Schuster, B.
- Venue
- 2012 IEEE International Conference on Robotics and Automation
- Publisher
- IEEE
- Published
- 2012-05
- Pages
- 3936-3943
- ISSN
- 1050-4729 (ISSN-L)
- OpenAlex
- W1990398405
- Cited by
- 647
- References
- 4
- FWCI
- 41.22
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Geiger, A., Moosmann, F., Car, O., & Schuster, B. (2012). Automatic camera and range sensor calibration using a single shot. 2012 IEEE International Conference on Robotics and Automation. https://doi.org/10.1109/icra.2012.6224570
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