The DOI matches its Crossref record; 29 of the 30 references it cites were found in a registry or an index.
A flexible new technique for camera calibration
Abstract
We propose a flexible technique to easily calibrate a camera. It only requires the camera to observe a planar pattern shown at a few (at least two) different orientations. Either the camera or the planar pattern can be freely moved. The motion need not be known. Radial lens distortion is modeled. The proposed procedure consists of a closed-form solution, followed by a nonlinear refinement based on the maximum likelihood criterion. Both computer simulation and real data have been used to test the proposed technique and very good results have been obtained. Compared with classical techniques which use expensive equipment such as two or three orthogonal planes, the proposed technique is easy to use and flexible. It advances 3D computer vision one more step from laboratory environments to real world use.
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“The widely used calibration method is proposed by Z. Zhang in [156] based on planar patterns at a few different orientations, where radial lens distortion is modelled.”
From Empowering things with intelligence: a survey of the progress, challenges, and opportunities in artificial intelligence of things (2021) · cites this paper as [156]
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Cites
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Three-dimensional computer vision: a geometric viewpoint
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Camera calibration with distortion models and accuracy evaluation
Weng, J., Cohen, P. R., & Herniou, M. (1992) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.159901 · Cited by 1,767
Camera self-calibration: Theory and experiments
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A theory of self-calibration of a moving camera
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Using vanishing points for camera calibration
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Sorted by citations
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
Scharstein, D., & Szeliski, R. (2002) · International Journal of Computer Vision · doi:10.1023/a:1014573219977 · Cited by 6,740
Flexible camera calibration by viewing a plane from unknown orientations
Zhang, Z. (1999) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.1999.791289 · Cited by 2,690
Self-citationMicrosoft Kinect Sensor and Its Effect
Zhang, Z. (2012) · IEEE Multimedia · doi:10.1109/mmul.2012.24 · Cited by 2,491
Self-citationHigh-quality video view interpolation using a layered representation
Zitnick, C. L., Kang, S. B., Uyttendaele, M., Winder, S. A. J., & Szeliski, R. (2004) · ACM Transactions on Graphics · doi:10.1145/1015706.1015766 · Cited by 1,386
Enhanced Computer Vision With Microsoft Kinect Sensor: A Review
Han, J., Shao, L., Xu, D., & Shotton, J. (2013) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2013.2265378 · Cited by 1,360
Metadata
- Authors
- Zhang, Z.
- Affiliations
- Microsoft (United States) (US)
- Corresponding author
- Zhang, Z.
- ORCID
- Zhang, Z.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 2000
- Volume
- 22
- Issue
- 11
- Pages
- 1330-1334
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W2167667767
- Cited by
- 15,004
- References
- 30
- Citations by year
- 2026: 858 · 2025: 1043 · 2024: 1031 · 2023: 1035 · 2022: 941 · 2021: 898 · 2020: 840 · 2019: 897 · 2018: 814 · 2017: 771 · 2016: 707 · 2015: 650 · 2014: 595 · 2013: 616 · 2012: 502
- FWCI
- 79.80
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Pattern Analysis and Machine Intelligence (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Optical measurement and interference techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Object Detection Techniques
- Keywords
- camera calibration, planar pattern, radial distortion, analytical solution, maximum likelihood refinement, 3D vision
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