The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
In defense of the eight-point algorithm
Abstract
The fundamental matrix is a basic tool in the analysis of scenes taken with two uncalibrated cameras, and the eight-point algorithm is a frequently cited method for computing the fundamental matrix from a set of eight or more point matches. It has the advantage of simplicity of implementation. The prevailing view is, however, that it is extremely susceptible to noise and hence virtually useless for most purposes. This paper challenges that view, by showing that by preceding the algorithm with a very simple normalization (translation and scaling) of the coordinates of the matched points, results are obtained comparable with the best iterative algorithms. This improved performance is justified by theory and verified by extensive experiments on real images.
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Cites
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A computer algorithm for reconstructing a scene from two projections
Longuet-Higgins, H. C. (1981) · Nature · doi:10.1038/293133a0 · Cited by 2,383
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Hildebrand, B. F. (1987) · Cited by 1,373
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Numerical Recipes in C: The Art of Scientific Computing
Seiler, M. C., & Seiler, F. A. (1989) · Risk Analysis · doi:10.1111/j.1539-6924.1989.tb01007.x · Cited by 1,346
What can be seen in three dimensions with an uncalibrated stereo rig?
Faugeras, O. D. (1992) · Lecture Notes in Computer Science · doi:10.1007/3-540-55426-2_61 · Cited by 839
Tsai, R. Y., & Huang, T. S. (1984) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.1984.4767471 · Cited by 828
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
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Cited by
An efficient solution to the five-point relative pose problem
Nister, D. (2004) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2004.17 · Cited by 2,009
Visual Modeling with a Hand-Held Camera
Pollefeys, M., Van Gool, L., Vergauwen, M., Verbiest, F., Cornelis, K., Tops, J., & Koch, R. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000025798.50602.3a · Cited by 874
Image matching across wide baselines: From paper to practice
Jin, Y., Mishkin, D., Mishchuk, A., Matas, J., Fua, P., Yi, K. M., & Trulls, E. (2021) · International Journal of Computer Vision · doi:10.1007/s11263-020-01385-0 · Cited by 388
An efficient solution to the five-point relative pose problem
Nister, D. (2003) · 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings. · doi:10.1109/cvpr.2003.1211470 · Cited by 279
Malis, E., & Chaumette, F. (2000) · International Journal of Computer Vision · doi:10.1023/a:1008181530296 · Cited by 273
Metadata
- Authors
- Hartley, R. I.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 1997-06
- Volume
- 19
- Issue
- 6
- Pages
- 580-593
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W2102481828
- Cited by
- 1,625
- References
- 24
- FWCI
- 25.73
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
