Critical Configurations for Radial Distortion Self-Calibration
Abstract
In this paper, we study the configurations of motion and structure that lead to inherent ambiguities in radial distortion estimation (or 3D reconstruction with unknown radial distortions). By analyzing the motion field of radially distorted images, we solve for critical surface pairs that can lead to the same motion field under different radial distortions and possibly different camera motions. We study the properties of the discovered critical configurations and discuss the practically important configurations that often occur in real applications. We demonstrate the impact of the radial distortion ambiguity on multi-view reconstruction with synthetic experiments and real experiments.
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A variety of inappropriate camera motions or environmental geometries can result in critical configurations which cannot be resolved by existing optimization schemes.
“Last but not least, a variety of inappropriate camera motions or environmental geometries can result in so-called critical configurations which cannot be resolved by the existing optimization schemes122.”
From Perspectives in machine learning for wildlife conservation (2022) · cites this paper as [122]
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Perspectives in machine learning for wildlife conservation
Tuia, D., Kellenberger, B., Beery, S., Costelloe, B. R., Zuffi, S., Risse, B., Mathis, A., Mathis, M. W., van Langevelde, F., Burghardt, T., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-27980-y · Cited by 740 · see citing works
Haalck, L., & Risse, B. (2021) · 2021 IEEE Winter Conference on Applications of Computer Vision (WACV) · doi:10.1109/wacv48630.2021.00189 · Cited by 3 · see citing works
- Authors
- Wu, C.
- Affiliations
- Google (United States) (US)
- Corresponding author
- Wu, Changchang
- Venue
- 2014 IEEE Conference on Computer Vision and Pattern Recognition
- Publisher
- IEEE
- Published
- 2014-06
- Pages
- 25-32
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2102000110
- Cited by
- 59
- References
- 24
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 2 · 2023: 2 · 2022: 5 · 2021: 5 · 2020: 5 · 2019: 6 · 2018: 5 · 2017: 10 · 2016: 5 · 2015: 9 · 2014: 2
- FWCI
- 4.66
- 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 › Computer Science › Computer Vision and Pattern Recognition › Optical measurement and interference techniques
- Physical Sciences › Earth and Planetary Sciences › Geology › 3D Surveying and Cultural Heritage
- Keywords
- radial distortion, self-calibration, critical configurations, ambiguity, 3D reconstruction, multi-view reconstruction, camera movement, motion field
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