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Bundle Adjustment — A Modern Synthesis
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“These are commonly referred to as landmark-based or feature-based representations, and have been widespread in mobile robotics since early work on localization and mapping, and in computer vision in the context of Structure from Motion [2, 244].”
From Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age (2016) · cites this paper as [244]
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Cites
Golub, G. (2012) · doi:10.56021/9781421407944 · Cited by 34,505
Multiple View Geometry in Computer Vision
Hartley, R., & Zisserman, A. (2004) · doi:10.1017/cbo9780511811685 · Cited by 21,070
Self-citationNocedal, J., & Wright, S. J. (1999) · Springer eBooks · doi:10.1007/b98874 · Cited by 9,563
Practical Methods of Optimization
Fletcher, R. (2000) · Wiley eBooks · doi:10.1002/9781118723203 · Cited by 7,649
Pattern Recognition and Neural Networks
Ripley, B. D. (1996) · Cambridge University Press eBooks · doi:10.1017/cbo9780511812651 · Cited by 6,500
A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs
Karypis, G., & Kumar, V. (1998) · SIAM Journal on Scientific Computing · doi:10.1137/s1064827595287997 · Cited by 5,984
Anderson, E., Bai, Z., Bischof, C., Blackford, L. S., Demmel, J., Dongarra, J. J., Croz, J. D., Greenbaum, A., Hammarling, S. J., McKenney, A., et al. (1999) · Society for Industrial and Applied Mathematics eBooks · doi:10.1137/1.9780898719604 · Cited by 4,493
Practical Methods of Optimization.
Witzgall, C., & Fletcher, R. (1989) · Mathematics of Computation · doi:10.2307/2008742 · Cited by 3,621
Templates for the Solution of Linear Systems: Building Blocks for Iterative Methods
Barrett, R. F., Berry, M., Chan, T. F.-C., Demmel, J. W., Donato, J. M., Dongarra, J. J., Eijkhout, V. L., Pozo, R., Romine, C. H., & van der Vorst, H. A. (1994) · Society for Industrial and Applied Mathematics eBooks · doi:10.1137/1.9781611971538 · Cited by 3,493
Numerical Methods for Least Squares Problems
Björck, Å. (1996) · Society for Industrial and Applied Mathematics eBooks · doi:10.1137/1.9781611971484 · Cited by 3,276
Research works printed but not linked: 22
- P. T. Boggs, R. H. Byrd, J. E. Rodgers, and R. B. Schnabel. Users reference guide for ODRPACK 2.01: Software for weighted orthogonal distance regression. Technical Report NISTIR 92-4834, NIST, Gaithersburg, MD, June 1992.
- R. J. Boscovich. De litteraria expeditione per pontificiam ditionem, et synopsis amplioris operis, ac habenturplura ejus ex exemplaria etiam sensorum impressa. Bononiensi Scientarum et Artum Instituto Atque Academia Commentarii, IV:353–396, 1757.
- D. C. Brown. Calibration of close range cameras. Int. Archives Photogrammetry, 19(5), 1972. Unbound paper (26 pages).
- D. C. Brown. The bundle adjustment — progress and prospects. Int. Archives Photogrammetry, 21(3), 1976. Paper number 3-03 (33 pages).
- W. Förstner. On the geometric precision of digital correlation. Int. Arch. Photogrammetry & Remote Sensing, 24(3): 176–189, 1982.
- W. Förstner. A feature-based correspondence algorithm for image matching. Int. Arch. Photogrammetry & Remote Sensing, 26(3/3): 150–166, 1984.
- W. Förstner. The reliability of block triangulation. Photogrammetric Engineering & Remote Sensing, 51(8): 1137–1149, 1985.
- P. Gill, W. Murray, and M. Wright. Practical Optimization. Academic Press, 1981.
- A. Grün. Accuracy, reliability and statistics in close range photogrammetry. In Inter-Congress Symposium of ISP Commission V, page Presented paper. Unbound paper No.9 (24 pages), Stockholm, 1978.
- A. Grün. Precision and reliability aspects in close range photogrammetry. Int. Arch. Photogrammetry, 11(23B):378–391, 1980.
- A. Grün. An optimum algorithm for on-line triangulation. In Symposium of Commission III of the ISPRS, Helsinki, 1982.
- A. Grün. Adaptive kleinste Quadrate Korrelation and geometrische Zusatzinformationen. Vermessung, Photogrammetrie, Kulturtechnik, 9(83):309–312, 1985.
- A. Grün. Algorithmic aspects of on-line triangulation. Photogrammetric Engineering & Remote Sensing, 4(51):419–436, 1985.
- M. S. Gyer. The inversion of the normal equations of analytical aerotriangulation by the method of recursive partitioning. Technical report, Rome Air Development Center, Rome, New York, 1967.
- R. Levy. Restructuring the structural stiffness matrix to improve computational efficiency. Jet Propulsion Lab. Technical Review, 1:61–70, 1971.
- M. X. Li. Hierarchical Multi-point Matching with Simultaneous Detection and Location of Breaklines. PhD thesis, KTH Stockholm, 1989.
- P. Meissl. Die innere Genauigkeit eines Punkthaufens. Österreichische Zeitschrift für Vermessungswesen, 50(5): 159–165 and 50(6): 186–194, 1962.
- E. Mikhail and R. Helmering. Recursive methods in photogrammetric data reduction. Photogrammetric Engineering, 39(9):983–989, 1973.
- E. Mittermayer. Zur Ausgleichung freier Netze. Zeitschrift für Vermessungswesen, 97(11):481–489, 1962.
- D. Rosenholm. Accuracy improvement of digital matching for elevation of digital terrain models. Int. Arch. Photogrammetry & Remote Sensing, 26(3/2):573–587, 1986.
- C. C. Slama, editor. Manual of Photo grammetry. American Society of Photogrammetry and Remote Sensing, Falls Church, Virginia, USA, 1980.
- B.P. Wrobel. Facets stereo vision (FAST vision) — a new approach to computer stereo vision and to digital photogrammetry. In ISPRS Intercommission Conf. Fast Processing of Photogrammetric Data, pages 231–258, Interlaken, Switzerland, June 1987.
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Camera calibration: active versus passive targets
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High-frequency shape and albedo from shading using natural image statistics
Barron, J. T., & Malik, J. (2011) · doi:10.1109/cvpr.2011.5995392 · Cited by 66
Quantitative Stereovision in a Scanning Electron Microscope
Zhu, T., Sutton, M. A., Li, N., Orteu, J., Cornille, N., Li, X., & Reynolds, A. P. (2010) · Experimental Mechanics · doi:10.1007/s11340-010-9378-7 · Cited by 66
Robust feature matching via support-line voting and affine-invariant ratios
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Goldlüecke, B., Aubry, M., Kolev, K., & Cremers, D. (2013) · International Journal of Computer Vision · doi:10.1007/s11263-013-0654-8 · Cited by 66
Mosaicking of Unmanned Aerial Vehicle Imagery in the Absence of Camera Poses
Xu, Y., Ou, J., He, H., Zhang, X., & Mills, J. P. (2016) · Remote Sensing · doi:10.3390/rs8030204 · Cited by 66
Zhang, Y., Teng, P., Shimizu, Y., Hosoi, F., & Omasa, K. (2016) · Sensors · doi:10.3390/s16060874 · Cited by 66
Provably-convergent iterative methods for projective structure from motion
Mahamud, S., Hebert, M., Omori, Y., & Ponce, J. (2005) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2001.990642 · Cited by 66
Incremental Fusion of Structure-from-Motion and GPS Using Constrained Bundle Adjustments
Lhuillier, M. (2012) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2012.157 · Cited by 65
Mahmood, B., Han, S., & Lee, D.-E. (2020) · Remote Sensing · doi:10.3390/rs12142302 · Cited by 64
Drap, P., Seinturier, J., Hijazi, B., Merad, D., Boï, J.-M., Chemisky, B., Seguin, E., & Long, L. (2015) · Journal on Computing and Cultural Heritage · doi:10.1145/2757283 · Cited by 65
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Strand, R., & Hayman, E. (2005) · British Machine Vision Conference (BMVC) · doi:10.5244/c.19.9 · Cited by 65
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Huang, G. P., Mourikis, A. I., & Roumeliotis, S. I. (2011) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2011.6095161 · Cited by 65
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Hesch, J. A., Kottas, D. G., Bowman, S. L., & Roumeliotis, S. I. (2013) · Springer tracts in advanced robotics · doi:10.1007/978-3-642-36279-8_34 · Cited by 64
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Labbé, Y., Carpentier, J., Aubry, M., & Šivic, J. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58520-4_34 · Cited by 472
Metadata
- Authors
- Triggs, B., McLauchlan, P. F., Hartley, R. I., & Fitzgibbon, A. W.
- Affiliations
- Institut national de recherche en sciences et technologies du numérique (FR)
- University of Surrey (GB)
- General Electric (United States) (US)
- University of Oxford (GB)
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2000
- Volume
- 1883
- Pages
- 298-372
- ISSN
- 0302-9743 (ISSN-L)
- OpenAlex
- W2124313187
- Cited by
- 3,988
- References
- 101
- Citations by year
- 2026: 79 · 2025: 137 · 2024: 196 · 2023: 190 · 2022: 201 · 2021: 236 · 2020: 231 · 2019: 239 · 2018: 204 · 2017: 222 · 2016: 178 · 2015: 220 · 2014: 194 · 2013: 187 · 2012: 189
- FWCI
- 41.85
- Type
- conference paper
- Language
- en
- Open access
- green
- inria.hal.science
- Licence
- Locations
- Lecture notes in computer science (publishedVersion)
- HAL (submittedVersion, other-oa)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Robotics and Sensor-Based Localization
- Physical Sciences › Earth and Planetary Sciences › Geology › 3D Surveying and Cultural Heritage
- Keywords
- bundle adjustment, photogrammetry, structure from motion, visual reconstruction, robust cost function, recursive optimization, gauge invariance, quality control, nonlinear least squares
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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.
Statistics and arithmetic are recomputed, not judged.
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