The DOI matches its Crossref record; 94 of the 101 references it cites were found in a registry or an index.
Bundle Adjustment — A Modern Synthesis
Open accessOverview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“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]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
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.
Cited by
Sorted by citations
Items 701–800 of 1,002
Subject-specific body segment parameter estimation using 3D photogrammetry with multiple cameras
Peyer, K. E., Morris, M., & Sellers, W. I. (2015) · PeerJ · doi:10.7717/peerj.831 · Cited by 44
Self-calibration of Scheimpflug cameras: an easy protocol
Louhichi, H., Fournel, T., Lavest, J., & Aïssia, H. B. (2007) · Measurement Science and Technology · doi:10.1088/0957-0233/18/8/037 · Cited by 44
Underwater environment reconstruction using stereo and inertial data
Hogue, A., German, A., & Jenkin, M. R. M. (2007) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/icsmc.2007.4413666 · Cited by 44
Object modeling using a ToF camera under an uncertainty reduction approach
Foix, S., Alenyà, G., Andrade‐Cetto, J., & Carme Torras, A. (2010) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/robot.2010.5509197 · Cited by 44
Generalized Subgraph Preconditioners for Large-Scale Bundle Adjustment
Jian, Y.-D., Balcan, D. C., & Dellaert, F. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-34091-8_6 · Cited by 44
Acoustic-inertial underwater navigation
Yang, Y., & Huang, G. P. (2017) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2017.7989571 · Cited by 44
Applications of low-cost 3D imaging techniques for the documentation of heritage objects
Morita, M. M., & Bilmes, G. M. (2018) · Optica Pura y Aplicada · doi:10.7149/opa.51.2.50026 · Cited by 44
Sadeghi‐Niaraki, A., & Choi, S.-M. (2020) · Sensors · doi:10.3390/s20102997 · Cited by 49
Dense Point Cloud Quality Factor as Proxy for Accuracy Assessment of Image-Based 3D Reconstruction
Javadnejad, F., Slocum, R. K., Gillins, D. T., Olsen, M. J., & Parrish, C. E. (2020) · Journal of Surveying Engineering · doi:10.1061/(asce)su.1943-5428.0000333 · Cited by 44
DPLVO: Direct Point-Line Monocular Visual Odometry
Zhou, L., Wang, S., & Kaess, M. (2021) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2021.3097052 · Cited by 42
Overview of deep learning application on visual SLAM
Li, S., Zhang, D., Xian, Y., Li, B., Zhang, T., & Zhong, C. (2022) · Displays · doi:10.1016/j.displa.2022.102298 · Cited by 47
Unified Computation of Strict Maximum Likelihood for Geometric Fitting
Kanatani, K., & Sugaya, Y. (2008) · Journal of Mathematical Imaging and Vision · doi:10.1007/s10851-010-0206-6 · Cited by 44
Yu, X., Jiang, N., Cheong, L., Leong, H. W., & Yan, X. (2008) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2008.01.006 · Cited by 44
Large-volume metrology instrument selection and measurability analysis
Muelaner, J. E., Cai, B., & Maropoulos, P. (2009) · Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture · doi:10.1243/09544054jem1676 · Cited by 44
Structure and kinematics triangulation with a rolling shutter stereo rig
Ait-Aider, O., & Berry, F. (2009) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2009.5459408 · Cited by 44
Spectral partitioning for structure from motion
Steedly, Essa, & Dellaert (2003) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2003.1238457 · Cited by 44
Untwisting a Projective Reconstruction
Nistér, D. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000029667.76852.a1 · Cited by 44
Towards visual ego-motion learning in robots
Pillai, S., & Leonard, J. J. (2017) · 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2017.8206441 · Cited by 42
A comprehensive overview of dynamic visual SLAM and deep learning: concepts, methods and challenges
Beghdadi, A., & Mallem, M. (2022) · Machine Vision and Applications · doi:10.1007/s00138-022-01306-w · Cited by 49
Marks, E., Magistri, F., & Stachniss, C. (2022) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra46639.2022.9811358 · Cited by 43
RoboTAP: Tracking Arbitrary Points for Few-Shot Visual Imitation
Vecerík, M., Doersch, C., Yang, Y., Davchev, T., Aytar, Y., Zhou, G., Hadsell, R. T., Agapito, L., & Scholz, J. (2024) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra57147.2024.10611409 · Cited by 44
DSM BASED ORIENTATION OF LARGE STEREO SATELLITE IMAGE BLOCKS
d’Angelo, P., & Reinartz, P. H. (2012) · The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences · doi:10.5194/isprsarchives-xxxix-b1-209-2012 · Cited by 43
Soons, J. A. M., Lava, P., Debruyne, D., & Dirckx, J. (2012) · Journal of the mechanical behavior of biomedical materials/Journal of mechanical behavior of biomedical materials · doi:10.1016/j.jmbbm.2012.05.004 · Cited by 43
Online calibration of stereo rigs for long-term autonomy
Warren, M., McKinnon, D. H., & Upcroft, B. (2013) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2013.6631096 · Cited by 43
The Pathfinder image-guided surgical robot
Deacon, G. B., Harwood, A., Holdback, J., Maiwand, D., Pearce, M., Reid, I. D., Street, M., & Taylor, J. (2009) · Proceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in Medicine · doi:10.1243/09544119jeim617 · Cited by 43
A Stable and Accurate Marker-Less Augmented Reality Registration Method
Gao, Q.-H., Wan, T.-R., Tang, W., & Chen, L. (2017) · International Conference on Cyberworlds · doi:10.1109/cw.2017.44 · Cited by 35
DeVito, Z., Mara, M., Zollhöfer, M., Bernstein, G., Ragan‐Kelley, J., Theobalt, C., Hanrahan, P., Fisher, M., & Nießner, M. (2017) · ACM Transactions on Graphics · doi:10.1145/3132188 · Cited by 43
DMS-SLAM: A General Visual SLAM System for Dynamic Scenes with Multiple Sensors
Liu, G.-H., Zeng, W.-L., Feng, B., & Xu, F. (2019) · Italian National Conference on Sensors · doi:10.3390/s19173714 · Cited by 43
Applications of structure from motion: a survey
Wei, Y., Kang, L., Yang, B., & Wu, L. (2013) · Frontiers of Information Technology & Electronic Engineering · doi:10.1631/jzus.cide1302 · Cited by 43
SchurVINS: Schur Complement-Based Lightweight Visual Inertial Navigation System
Fan, Y., Zhao, T., & Wang, G. (2024) · 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/cvpr52733.2024.01701 · Cited by 42
Leveraging Image‐based Localization for Infrastructure‐based Calibration of a Multi‐camera Rig
Heng, L., Furgale, P., & Pollefeys, M. (2014) · Journal of Field Robotics · doi:10.1002/rob.21540 · Cited by 42
Review and classification of vision-based localisation techniques in unknown environments
Ben-Afia, A., Deambrogio, L., Salos, D., Escher, A.-C., Macabiau, C., Soulier, L., & Gay-Bellile, V. (2014) · IET Radar Sonar & Navigation · doi:10.1049/iet-rsn.2013.0389 · Cited by 43
Closing the loop in appearance-guided omnidirectional visual odometry by using vocabulary trees
Scaramuzza, D., Fraundorfer, F., & Pollefeys, M. (2010) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2010.02.013 · Cited by 42
Robust Absolute Rotation Estimation via Low-Rank and Sparse Matrix Decomposition
Arrigoni, F., Magri, L., Rossi, B., Fragneto, P., & Fusiello, A. (2014) · International Conference on 3D Vision (3DV) · doi:10.1109/3dv.2014.48 · Cited by 42
Exploiting distinctive visual landmark maps in pan–tilt–zoom camera networks
Bimbo, A. D., Dini, F., Lisanti, G., & Pernici, F. (2010) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2010.01.007 · Cited by 41
Bae, H., Golparvar‐Fard, M., & White, J. (2014) · Journal of Computing in Civil Engineering · doi:10.1061/(asce)cp.1943-5487.0000392 · Cited by 42
Virtual Visual Servoing for Multicamera Pose Estimation
Assa, A., & Janabi‐Sharifi, F. (2014) · IEEE/ASME Transactions on Mechatronics · doi:10.1109/tmech.2014.2305916 · Cited by 42
Lampert, C. H., & Peters, J. (2010) · Journal of Real-Time Image Processing · doi:10.1007/s11554-010-0168-3 · Cited by 42
Lisein, J., Linchant, J., Lejeune, P., Bouché, P., & Vermeulen, C. (2013) · Tropical Conservation Science · doi:10.1177/194008291300600405 · Cited by 42
An Evaluation of Video-to-Video Face Verification
Poh, N., Chan, C. H., Kittler, J., Marcel, S., Cool, C. M., Rúa, E. A., Alba‐Castro, J. L., Villegas, M., Paredes, R., Štruc, V., et al. (2010) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2010.2077627 · Cited by 42
Large Scale Image Mosaic Construction for Agricultural Applications
Li, Z., & Isler, V. (2016) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2016.2519946 · Cited by 42
Lu, B., He, Y., & Liu, H. H. T. (2017) · International Journal of Remote Sensing · doi:10.1080/01431161.2017.1363441 · Cited by 42
Capolupo, A., Kooistra, L., & Boccia, L. (2018) · International Journal of Applied Earth Observation and Geoinformation · doi:10.1016/j.jag.2018.08.008 · Cited by 42
Camera marker networks for articulated machine pose estimation
Feng, C., Kamat, V. R., & Cai, H. (2018) · Automation in Construction · doi:10.1016/j.autcon.2018.09.004 · Cited by 42
Smartphone-Based Photogrammetry for the 3D Modeling of a Geomorphological Structure
Dabove, P., Grasso, N., & Piras, M. (2019) · Applied Sciences · doi:10.3390/app9183884 · Cited by 42
Automatic TEM image alignment by trifocal geometry
Brandt, S. S., & Ziese, U. (2006) · Journal of Microscopy · doi:10.1111/j.1365-2818.2006.01545.x · Cited by 42
Visual SLAM for Unmanned Aerial Vehicles: Localization and Perception
Zhuang, L., Zhong, X., Xu, L., Tian, C., & Yu, W.-S. (2024) · Italian National Conference on Sensors · doi:10.3390/s24102980 · Cited by 46
Clement, L., Peretroukhin, V., Lambert, J., & Kelly, J. W. (2015) · Canadian Conference on Computer and Robot Vision · doi:10.1109/crv.2015.11 · Cited by 41
Study of the uncertainty of angle measurement for a rotary-laser automatic theodolite (R-LAT)
Muelaner, J. E., Wang, Z., Jamshidi, J., Maropoulos, P., Mileham, A. R., Hughes, B., & Forbes, A. (2008) · Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture · doi:10.1243/09544054jem1272 · Cited by 41
Robust Locally Linear Analysis with Applications to Image Denoising and Blind Inpainting
Wang, Y., Szlam, A. D., & Lerman, G. (2013) · SIAM Journal on Imaging Sciences · doi:10.1137/110843642 · Cited by 41
Using depth in visual simultaneous localisation and mapping
Scherer, S., Dube, D., & Zell, A. (2012) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2012.6224864 · Cited by 41
Tscharf, A., Rumpler, M., Fraundorfer, F., Mayer, G., & Bischof, H. (2015) · ISPRS annals of the photogrammetry, remote sensing and spatial information sciences · doi:10.5194/isprsannals-ii-1-w1-15-2015 · Cited by 41
A minimal solution to the rolling shutter pose estimation problem
Saurer, O., Pollefeys, M., & Lee, G. H. (2015) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2015.7353540 · Cited by 41
Cornic, P., Illoul, C., Cheminet, A., Besnerais, G. L., Champagnat, F., Sant, Y. L., & Leclaire, B. (2016) · Measurement Science and Technology · doi:10.1088/0957-0233/27/9/094004 · Cited by 41
Daakir, M., Marc Pierrot-deseilligny, A., Bosser, P., Pichard, F., Thom, C., Rabot, Y., & Martin, O. (2017) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2016.12.007 · Cited by 41
Kang, L., Wu, L., Wei, Y., Lao, S., & Yang, Y. (2017) · Pattern Recognition · doi:10.1016/j.patcog.2017.04.006 · Cited by 41
Rapid 3D Reconstruction for Image Sequence Acquired from UAV Camera
Qu, Y., Huang, J., & Zhang, X. (2018) · Sensors · doi:10.3390/s18010225 · Cited by 42
Sayab, M., Aerden, D., Paananen, M., & Saarela, P. (2018) · Remote Sensing · doi:10.3390/rs10081296 · Cited by 41
Calì, M., & Ambu, R. (2018) · Sensors · doi:10.3390/s18092815 · Cited by 41
Depth Completion via Deep Basis Fitting
Qu, C., Nguyen, T., & Taylor, C. J. (2020) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv45572.2020.9093349 · Cited by 43
Using UAV and LiDAR data for gully geomorphic changes monitoring
Niculiță, M., Mărgărint, M. C., & Tarolli, P. (2020) · Developments in earth surface processes · doi:10.1016/b978-0-444-64177-9.00010-2 · Cited by 41
Monitoring the Dynamics of a Helicopter Main Rotor With High-Speed Stereophotogrammetry
Lundström, T. S., Baqersad, J., & Niezrecki, C. (2016) · Experimental Techniques · doi:10.1007/s40799-016-0092-y · Cited by 41
Localization of Mobile Robots Using Odometry and an External Vision Sensor
Pizarro, D., Mazo, M., Santiso, E., Marrón-Romera, M., Jimenez, D., Cóbreces, S., & Losada-Gutiérrez, C. (2010) · Sensors · doi:10.3390/s100403655 · Cited by 41
A Multi-camera, Multi-projector Super-Resolution Framework for Structured Light
Weinmann, M., Schwartz, C., Ruiters, R., & Klein, R. (2011) · International Conference on 3D Imaging, Modeling, Processing, Visualization & Transmission · doi:10.1109/3dimpvt.2011.57 · Cited by 41
Segmenting, modeling, and matching video clips containing multiple moving objects
Rothganger, F., Lazebnik, S., Schmid, C., & Ponce, J. (2004) · 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.2004.1315263 · Cited by 40
Learn to Dance with AIST++: Music Conditioned 3D Dance GenerationPreprint
Li, R., Yang, S., Ross, D. A., & Kanazawa, A. (2021) · arXiv (Cornell University) · Cited by 45
MASt3R-SfM: A Fully-Integrated Solution for Unconstrained Structure-from-Motion
Duisterhof, B. P., Žust, L., Weinzaepfel, P., Leroy, V., Cabon, Y., & Revaud, J. (2025) · International Conference on 3D Vision (3DV) · doi:10.1109/3dv66043.2025.00008 · Cited by 43
A Survey of Distributed Computer Vision Algorithms
Radke, R. J. (2009) · Springer eBooks · doi:10.1007/978-0-387-93808-0_2 · Cited by 40
Fast topology estimation for image mosaicing using adaptive information thresholding
Elibol, A., Gracias, N., & García, R. (2012) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2012.10.010 · Cited by 40
Inspection of Complex Objects Using Multiple-X-Ray Views
Mery, D. (2014) · IEEE/ASME Transactions on Mechatronics · doi:10.1109/tmech.2014.2311032 · Cited by 40
Landmark based localization in urban environment
Qu, X., Soheilian, B., & Nicolas Paparoditis, A. (2017) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2017.09.010 · Cited by 40
Rolling Shutter Correction in Manhattan World
Purkait, P., Zach, C., & Leonardis, A. (2017) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.101 · Cited by 40
3D Reconstruction of Whole Stomach from Endoscope Video Using Structure-from-Motion
Widya, A. R., Monno, Y., Imahori, K., Okutomi, M., Suzuki, S., Gotoda, T., & Miki, K. (2019) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2019.8857964 · Cited by 41
Maximum likelihood mapping with spectral image registration
Pfingsthorn, M. F., Birk, A., Schwertfeger, S., Bülow, H., & Pathak, K. (2010) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/robot.2010.5509366 · Cited by 42
Robust multi-view feature matching from multiple unordered views
Yao, J., & Cham, W.-K. (2007) · Pattern Recognition · doi:10.1016/j.patcog.2007.02.011 · Cited by 39
Fast incremental square root information smoothing
Kaess, M., Ranganathan, A., & Dellaert, F. (2007) · Cited by 40
Error Characterization of the Factorization Method
Sun, Z. H., Ramesh, V., & Tekalp, A. M. (2001) · Computer Vision and Image Understanding · doi:10.1006/cviu.2001.0910 · Cited by 40
Shape, Illumination, and Reflectance from Shading
Barron, J. T., & Malik, J. (2013) · doi:10.21236/ada586648 · Cited by 40
3D reconstruction of spherical images: a review of techniques, applications, and prospects
Jiang, S., You, K., Li, Y., Weng, D., & Chen, W. (2024) · Geo-spatial Information Science · doi:10.1080/10095020.2024.2313328 · Cited by 41
An Adaptive Lighting Indoor vSLAM With Limited On-Device Resources
Hu, Z., Qi, W., Ding, K., Liu, G., & Zhao, Y. (2024) · IEEE Internet of Things Journal · doi:10.1109/jiot.2024.3406816 · Cited by 41
Meilland, M., Comport, A., & Rives, P. (2015) · J. Field Robotics · doi:10.1002/rob.21531 · Cited by 45
Jaklič, A., Erič, M., Mihajlović, I., Stopinšek, Ž., & Solina, F. (2015) · Journal of Archaeological Science · doi:10.1016/j.jas.2015.08.007 · Cited by 39
An analytical least-squares solution to the odometer-camera extrinsic calibration problem
Guo, C., Mirzaei, F. M., & Roumeliotis, S. I. (2012) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2012.6225339 · Cited by 39
Extrinsic Calibration of Camera Networks Using a Sphere
Guan, J., Deboeverie, F., Slembrouck, M., Haerenborgh, D. V., Cauwelaert, D. V., Veelaert, P., & Philips, W. R. (2015) · Sensors · doi:10.3390/s150818985 · Cited by 39
Visual SLAM with a RGB-D Camera on a Quadrotor UAV Using on-Board Processing
Aguilar, W. G., Rodríguez, G. A., Alvarez, L. G., Sandoval, S., Quisaguano, F. J., & Limaico, A. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-59147-6_51 · Cited by 39
Piao, J.-C., & Kim, S.-D. (2017) · Italian National Conference on Sensors · doi:10.3390/s17112567 · Cited by 40
Integrating geometric models, site images and GIS based on Google Earth and Keyhole Markup Language
Li, D., & Lu, M. (2018) · Automation in Construction · doi:10.1016/j.autcon.2018.02.002 · Cited by 39
3D Reconstruction of Background and Objects Moving on Ground Plane Viewed from a Moving Camera
Chang, Y., & Medioni, G. G. (2006) · 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.2006.16 · Cited by 39
Calibration of Non-Overlapping Cameras---Application to Vision-Based Robotics
Lébraly, P., Royer, E., Ait-Aider, O., & Dhome, M. (2010) · British Machine Vision Conference (BMVC) · doi:10.5244/c.24.10 · Cited by 39
The effects of translational misalignment when self-calibrating rotating and zooming cameras
Hayman, E., & Murray, D. W. (2003) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2003.1217605 · Cited by 39
Parallel Tracking and Mapping with Multiple Cameras on an Unmanned Aerial Vehicle
Harmat, A., Sharf, I., & Trentini, M. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-33509-9_42 · Cited by 39
Key Issues in Modeling of Complex 3D Structures from Video Sequences
Chen, S., Wang, Y., & Cattani, C. (2011) · Mathematical Problems in Engineering · doi:10.1155/2012/856523 · Cited by 38
Rapid in-flight image quality check for UAV-enabled bridge inspection
Wang, F., Zou, Y., Chen, X., Zhang, C., Hou, L., Castillo, E. D. R., & Lim, J. B. P. (2024) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2024.05.008 · Cited by 40
CloudCV: Large-Scale Distributed Computer Vision as a Cloud Service
Agrawal, H., Mathialagan, C. S., Goyal, Y., Chavali, N., Banik, P., Mohapatra, A., Osman, A., & Batra, D. (2015) · Springer eBooks · doi:10.1007/978-3-319-24702-1_11 · Cited by 38
Homography-based planar mapping and tracking for mobile phones
Pirchheim, C., & Reitmayr, G. (2011) · Proceedings - International Symposium on Mixed and Augmented Reality, ISMAR · doi:10.1109/ismar.2011.6092367 · Cited by 37
Highly accurate 3D surface models by sparse surface adjustment
Ruhnke, M., Kummerle, R., Grisetti, G., & Burgard, W. (2012) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2012.6225077 · Cited by 38
A marker-free automatic alignment method based on scale-invariant features
Han, R., Zhang, F., Wan, X., Fernández, J., Sun, F., & Liu, Z. (2014) · Journal of Structural Biology · doi:10.1016/j.jsb.2014.02.011 · Cited by 38
Reconstructing 3-D Skin Surface Motion for the DIET Breast Cancer Screening System
Botterill, T., Lotz, T., Kashif, A. S., & Chase, J. G. (2014) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2014.2304959 · Cited by 38
Flight Dynamics-Based Recovery of a UAV Trajectory Using Ground Cameras
Rozantsev, A., Sinha, S. N., Dey, D., & Fua, P. (2017) · 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.2017.266 · Cited by 38
Multi-view 3D reconstruction and modeling of the unknown 3D scenes using genetic algorithms
Merras, M., Saaidi, A., Akkad, N. E., & Satori, K. (2017) · Soft Computing · doi:10.1007/s00500-017-2966-z · Cited by 38
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
About these checks
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
