The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
A Flexible Technique for Accurate Omnidirectional Camera Calibration and Structure from Motion
Open accessAbstract
In this paper, we present a flexible new technique for single viewpoint omnidirectional camera calibration. The proposed method only requires the camera to observe a planar pattern shown at a few different orientations. Either the camera or the planar pattern can be freely moved. No a priori knowledge of the motion is required, nor a specific model of the omnidirectional sensor. The only assumption is that the image projection function can be described by a Taylor series expansion whose coefficients are estimated by solving a two-step least-squares linear minimization problem. To test the proposed technique, we calibrated a panoramic camera having a field of view greater than 200 in the vertical direction, and we obtained very good results. To investigate the accuracy of the calibration, we also used the estimated omni-camera model in a structure from motion experiment. We obtained a 3D metric reconstruction of a scene from two highly distorted omnidirectional images by using image correspondences only. Compared with classical techniques, which rely on a specific parametric model of the omnidirectional camera, the proposed procedure is independent of the sensor, easy to use, and flexible.
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Cites
A flexible new technique for camera calibration
Zhang, Z. (2000) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.888718 · Cited by 15,004
A computer algorithm for reconstructing a scene from two projections
Longuet-Higgins, H. C. (1981) · Nature · doi:10.1038/293133a0 · Cited by 2,383
In defence of the 8-point algorithm
Hartley, R. I. (2002) · Proceedings of IEEE International Conference on Computer Vision · doi:10.1109/iccv.1995.466816 · Cited by 649
A Theory of Single-Viewpoint Catadioptric Image Formation
Baker, S., & Nayar, S. K. (1999) · International Journal of Computer Vision · doi:10.1023/a:1008128724364 · Cited by 610
Self-Calibration of a Moving Camera from Point Correspondences and Fundamental Matrices
Luong, Q.-T., & Faugeras, O. D. (1997) · International Journal of Computer Vision · doi:10.1023/a:1007982716991 · Cited by 389
A theory of catadioptric image formation
Baker, S., & Nayar, S. K. (2002) · Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271) · doi:10.1109/iccv.1998.710698 · Cited by 377
From projective to Euclidean space under any practical situation, a criticism of self-calibration
Bougnoux, S. (2002) · Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271) · doi:10.1109/iccv.1998.710808 · Cited by 230
Ego-motion and omnidirectional cameras
Gluckman, J., & Nayar, S. K. (2002) · Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271) · doi:10.1109/iccv.1998.710838 · Cited by 210
Epipolar Geometry for Central Catadioptric Cameras
Svoboda, T., & Pajdla, T. (2002) · International Journal of Computer Vision · doi:10.1023/a:1019869530073 · Cited by 197
Paracatadioptric camera calibration
Geyer, C., & Daniilidis, K. (2002) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.1000241 · Cited by 197
Estimation of omnidirectional camera model from epipolar geometry
Micusik, B., & Pajdla, T. (2003) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2003.1211393 · Cited by 154
Caustics of catadioptric cameras
Swaminathan, R., Grossberg, M. D., & Nayar, S. K. (2002) · IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2001.937581 · Cited by 109
Autocalibration & 3D reconstruction with non-central catadioptric cameras
Micusik, B., & Pajdla, T. (2004) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2004.1315014 · Cited by 96
Cited by
Scaramuzza, D., & Fraundorfer, F. (2011) · IEEE Robotics & Automation Magazine · doi:10.1109/mra.2011.943233 · Cited by 1,550
Self-citationAppearance-Guided Monocular Omnidirectional Visual Odometry for Outdoor Ground Vehicles
Scaramuzza, D., & Siegwart, R. (2008) · IEEE Transactions on Robotics · doi:10.1109/tro.2008.2004490 · Cited by 292
Self-citationLarge-scale direct SLAM for omnidirectional cameras
Caruso, D., Engel, J., & Cremers, D. (2015) · 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2015.7353366 · Cited by 244
Learning to Calibrate Straight Lines for Fisheye Image Rectification
Xue, Z., Xue, N., Xia, G.-S., & Shen, W. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00174 · Cited by 94
Metadata
- Authors
- Scaramuzza, D., Martinelli, A., & Siegwart, R.
- Venue
- Fourth IEEE International Conference on Computer Vision Systems (ICVS'06)
- Publisher
- IEEE
- Published
- 2006
- Pages
- 45-45
- OpenAlex
- W2099343826
- Cited by
- 417
- References
- 13
- FWCI
- 12.16
- Type
- conference paper
- Language
- en
- Open access
- green
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