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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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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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