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Fast and globally convergent pose estimation from video images
Abstract
Determining the rigid transformation relating 2D images to known 3D geometry is a classical problem in photogrammetry and computer vision. Heretofore, the best methods for solving the problem have relied on iterative optimization methods which cannot be proven to converge and/or which do not effectively account for the orthonormal structure of rotation matrices. We show that the pose estimation problem can be formulated as that of minimizing an error metric based on collinearity in object (as opposed to image) space. Using object space collinearity error, we derive an iterative algorithm which directly computes orthogonal rotation matrices and which is globally convergent. Experimentally, we show that the method is computationally efficient, that it is no less accurate than the best currently employed optimization methods, and that it outperforms all tested methods in robustness to outliers.
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Cites
Fischler, M. A., & Bolles, R. C. (1981) · Communications of the ACM · doi:10.1145/358669.358692 · Cited by 25,893
Cited by
EPnP: An Accurate O(n) Solution to the PnP Problem
Lepetit, V., Moreno-Noguer, F., & Fua, P. (2009) · International Journal of Computer Vision · doi:10.1007/s11263-008-0152-6 · Cited by 3,298
SBA: A software package for generic sparse bundle adjustment
Lourakis, M. I. A., & Argyros, A. A. (2009) · ACM Transactions on Mathematical Software · doi:10.1145/1486525.1486527 · Cited by 788
Pose estimation for augmented reality: a hands-on survey
Marchand, E., Uchiyama, H., & Spindler, F. (2016) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2015.2513408 · Cited by 746
A Robust O(n) Solution to the Perspective-n-Point Problem
Li, S., Xu, C., & Xie, M. (2012) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2012.41 · Cited by 503
Accurate Non-Iterative O(n) Solution to the PnP Problem
Moreno-Noguer, F., Lepetit, V., & Fua, P. (2007) · 2007 IEEE 11th International Conference on Computer Vision · doi:10.1109/iccv.2007.4409116 · Cited by 295
Metadata
- Authors
- Lu, C.-P., Hager, G. D., & Mjolsness, E.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 2000-06
- Volume
- 22
- Issue
- 6
- Pages
- 610-622
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W2162440713
- Cited by
- 882
- References
- 1
- FWCI
- 15.34
- Type
- journal article
- Language
- en
- Open access
- closed
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- Lu, C.-P., Hager, G. D., & Mjolsness, E. (2000). Fast and globally convergent pose estimation from video images. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/34.862199
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