The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Autocalibration from planar scenes
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Citations
Cites
Ballard, D. H., & Brown, C. M. (1982) · Cited by 5,303
Camera self-calibration: Theory and experiments
Faugeras, O. D., Luong, Q. T., & Maybank, S. J. (1992) · Lecture Notes in Computer Science · doi:10.1007/3-540-55426-2_37 · Cited by 946
A theory of self-calibration of a moving camera
Maybank, S. J., & Faugeras, O. D. (1992) · International Journal of Computer Vision · doi:10.1007/bf00127171 · Cited by 820
Algebraic Projective Geometry.
Atchison, W. F., Semple, J. G., & Kneebone, G. T. (1953) · The American Mathematical Monthly · doi:10.2307/2307420 · Cited by 704
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
A factorization based algorithm for multi-image projective structure and motion
Sturm, P., & Triggs, B. (1996) · Lecture Notes in Computer Science · doi:10.1007/3-540-61123-1_183 · Cited by 578
Self-citationStatistical Optimization for Geometric Computation: Theory and Practice
(1996) · Machine Intelligence and Pattern Recognition · doi:10.1016/s0923-0459(96)x8019-4 · Cited by 483
Self-calibration from multiple views with a rotating camera
Hartley, R. I. (1994) · Lecture Notes in Computer Science · doi:10.1007/3-540-57956-7_52 · Cited by 315
Stratification of three-dimensional vision: projective, affine, and metric representations
Faugeras, O. D. (1995) · Journal of the Optical Society of America A · doi:10.1364/josaa.12.000465 · Cited by 305
Critical motion sequences for monocular self-calibration and uncalibrated Euclidean reconstruction
Sturm, P. (2002) · Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.1997.609467 · Cited by 228
Cited by
A flexible new technique for camera calibration
Zhang, Z. (2000) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.888718 · Cited by 15,004
Appearance-Guided Monocular Omnidirectional Visual Odometry for Outdoor Ground Vehicles
Scaramuzza, D., & Siegwart, R. (2008) · IEEE Transactions on Robotics · doi:10.1109/tro.2008.2004490 · Cited by 292
Combining two-view constraints for motion estimation
Govindu, V. M. (2005) · Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001 · doi:10.1109/cvpr.2001.990963 · Cited by 196
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
Large-Area Photo-Mosaics Using Global Alignment and Navigation Data
Ferrer, J., Elibol, A., Delaunoy, O., Gracias, N., & Garcia, R. (2007) · OCEANS 2007 · doi:10.1109/oceans.2007.4449367 · Cited by 67
Metadata
- Authors
- Triggs, B.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 1998
- Pages
- 89-105
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W1598118858
- Cited by
- 356
- References
- 11
- FWCI
- 15.87
- Type
- conference paper
- Language
- en
- Open access
- green
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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- Triggs, B. (1998). Autocalibration from planar scenes. Lecture Notes in Computer Science. https://doi.org/10.1007/bfb0055661
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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.
