An efficient solution to the five-point relative pose problem
Abstract
An efficient algorithmic solution to the classical five-point relative pose problem is presented. The problem is to find the possible solutions for relative camera motion between two calibrated views given five corresponding points. The algorithm consists of computing the coefficients of a tenth degree polynomial and subsequently finding its roots. It is the first algorithm well suited for numerical implementation that also corresponds to the inherent complexity of the problem. The algorithm is used in a robust hypothesis-and-test framework to estimate structure and motion in real-time.
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Multiple View Geometry in Computer Vision
Hartley, R., & Zisserman, A. (2004) · doi:10.1017/cbo9780511811685 · Cited by 21,070 · see citing works
Bundle Adjustment — A Modern Synthesis
Triggs, B., McLauchlan, P. F., Hartley, R. I., & Fitzgibbon, A. W. (2000) · Lecture Notes in Computer Science · doi:10.1007/3-540-44480-7_21 · Cited by 3,988 · see citing works
The Problem of Degeneracy in Structure and Motion Recovery from Uncalibrated Image Sequences
Torr, P. H. S., Fitzgibbon, A. W., & Zisserman, A. (1999) · International Journal of Computer Vision · doi:10.1023/a:1008140928553 · Cited by 156 · see citing works
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Scaramuzza, D., & Fraundorfer, F. (2011) · IEEE Robotics & Automation Magazine · doi:10.1109/mra.2011.943233 · Cited by 1,550 · see citing works
Two years of Visual Odometry on the Mars Exploration Rovers
Maimone, M., Cheng, Y., & Matthies, L. (2007) · Journal of Field Robotics · doi:10.1002/rob.20184 · Cited by 655 · see citing works
Visual Odometry : Part II: Matching, Robustness, Optimization, and Applications
Fraundorfer, F., & Scaramuzza, D. (2012) · IEEE Robotics & Automation Magazine · doi:10.1109/mra.2012.2182810 · Cited by 620 · see citing works
Get Out of My Lab: Large-scale, Real-Time Visual-Inertial Localization
Lynen, S., Sattler, T., Bosse, M., Hesch, J., Pollefeys, M., & Siegwart, R. (2015) · Robotics: Science and Systems XI · doi:10.15607/rss.2015.xi.037 · Cited by 243 · see citing works
Visual Odometry Revisited: What Should Be Learnt?
Zhan, H., Weerasekera, C. S., Bian, J.-W., & Reid, I. (2020) · 2020 IEEE International Conference on Robotics and Automation (ICRA) · doi:10.1109/icra40945.2020.9197374 · Cited by 201 · see citing works
DF-VO: What Should Be Learnt for Visual Odometry?
Zhan, H., Weerasekera, C. S., Bian, J.-W., Garg, R., & Reid, I. (2021) · arXiv · doi:10.48550/arxiv.2103.00933 · Cited by 31 · see citing works
- Authors
- Nister, D.
- Venue
- 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings.
- Publisher
- IEEE Comput. Soc
- Published
- 2003-12-22
- Volume
- 2
- Pages
- II-195-202
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2142876261
- Cited by
- 279
- References
- 3
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 3 · 2023: 5 · 2022: 7 · 2021: 9 · 2020: 21 · 2019: 6 · 2018: 14 · 2017: 19 · 2016: 9 · 2015: 19 · 2014: 10 · 2013: 19 · 2012: 22
- FWCI
- 11.01
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
- Physical Sciences › Engineering › Aerospace Engineering › Robotics and Sensor-Based Localization
- Physical Sciences › Earth and Planetary Sciences › Geology › 3D Surveying and Cultural Heritage
- Keywords
- corresponding points, polynomial root finding, hypothesis testing, real-time estimation
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Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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