Using many cameras as one
Abstract
We illustrate how to consider a network of cameras as a single generalized camera in a framework proposed by Nayar (2001). We derive the discrete structure from motion equations for generalized cameras, and illustrate the corollaries to epipolar geometry. This formal mechanism allows one to use a network of cameras as if they were a single imaging device, even when they do not share a common center of projection. Furthermore, an analysis of structure from motion algorithms for this imaging model gives constraints on the optimal design of panoramic imaging systems constructed from multiple cameras.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
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?
The task of soiling detection was first defined in [56].
“The task of soiling detection was to our best knowledge first defined in [56].”
From WoodScape: A Multi-Task, Multi-Camera Fisheye Dataset for Autonomous Driving (2019) · cites this paper as [56]
Cites
A Theory of Single-Viewpoint Catadioptric Image Formation
Baker, S. J., & Nayar, S. K. (1999) · International Journal of Computer Vision · doi:10.1023/a:1008128724364 · Cited by 613 · see citing works
Gupta, R., & Hartley, R. I. (1997) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.615446 · Cited by 420 · see citing works
A general imaging model and a method for finding its parameters
Grossberg, M. D., & Nayar, S. K. (2002) · IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2001.937611 · Cited by 276 · see citing works
Inherent ambiguities in recovering 3-D motion and structure from a noisy flow field
Adiv, G. (1989) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.24780 · Cited by 271 · see citing works
Ego-motion and omnidirectional cameras
Gluckman, J., & Nayar, S. K. (2002) · doi:10.1109/iccv.1998.710838 · Cited by 211 · see citing works
XVII. On a new geometry of space
Plucker, J. (1865) · Philosophical Transactions of the Royal Society of London · doi:10.1098/rstl.1865.0017 · Cited by 163 · see citing works
Epipolar geometry for panoramic cameras
Svoboda, T., Pajdla, T., & Hlaváč, V. (1998) · Lecture notes in computer science · doi:10.1007/bfb0055669 · Cited by 154 · see citing works
The Space of All Stereo Images
Seitz, S. M., & Kim, J. (2002) · International Journal of Computer Vision · doi:10.1023/a:1014851111084 · Cited by 145 · see citing works
Nelson, R. C., & Aloimonos, J. Y. (1988) · Biological Cybernetics · doi:10.1007/bf00364131 · Cited by 119 · see citing works
Caustics of catadioptric cameras
Swaminathan, R., Grossberg, M. D., & Nayar, S. K. (2002) · IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2001.937581 · Cited by 109 · see citing works
Planar catadioptric stereo: geometry and calibration
Gluckman, J., & Nayar, S. K. (2003) · 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.1999.786912 · Cited by 107 · see citing works
Understanding noise sensitivity in structure from motion
Daniilidis, K., & Spetsakis, M. E. (1996) · Cited by 92 · see citing works
Structure and motion from uncalibrated catadioptric views
Geyer, C., & Daniilidis, K. (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.2001.990487 · Cited by 84 · see citing works
Pajdla, T. (2002) · International Journal of Computer Vision · doi:10.1023/a:1014593824520 · Cited by 79 · see citing works
Shum, H., Kalai, A. T., & Seitz, S. M. (1999) · IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.1999.791193 · Cited by 78 · see citing works
Mixing catadioptric and perspective cameras
Sturm, P. F. (2003) · doi:10.1109/omnvis.2002.1044489 · Cited by 74 · see citing works
Omni-directional structure from motion
Chang, P., & Hebert, M. (2002) · doi:10.1109/omnvis.2000.853819 · Cited by 66 · see citing works
Optimal structure from motion: local ambiguities and global estimates
Soatto, S., & Brockett, R. W. (2002) · 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.1998.698621 · Cited by 59 · see citing works
The space of all stereo images
Seitz, S. M. (2002) · IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2001.937495 · Cited by 55 · see citing works
Catadioptric sensors that approximate wide-angle perspective projections
Hicks, R. A., & Bajcsy, R. K. (2002) · doi:10.1109/omnvis.2000.853813 · Cited by 54 · see citing works
Catadioptric sensors that approximate wide-angle perspective projections
Hicks, R. A., & Bajcsy, R. K. (2002) · 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.2000.855867 · Cited by 48 · see citing works
A spherical eye from multiple cameras (makes better models of the world)
Baker, P., Fermüller, C., Aloimonos, Y., et al. (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.2001.990525 · Cited by 47 · see citing works
Properties of the Catadioptric Fundamental Matrix
Geyer, C., & Daniilidis, K. (2002) · Lecture notes in computer science · doi:10.1007/3-540-47967-8_10 · Cited by 42 · see citing works
Directions of Motion Fields are Hardly Ever Ambiguous
Brodský, T., Fermüller, C., & Aloimonos, Y. (1998) · International Journal of Computer Vision · doi:10.1023/a:1007928406666 · Cited by 40 · see citing works
Acquisition of three-dimensional information using omnidirectional stereo vision
Chaen, A., Yamazawa, K., Yokoya, N., et al. (1997) · Lecture notes in computer science · doi:10.1007/3-540-63930-6_133 · Cited by 11 · see citing works
New Eyes for Shape and Motion Estimation
Baker, P., Pless, R. B., Fermüller, C., et al. (2000) · Lecture notes in computer science · doi:10.1007/3-540-45482-9_12 · Cited by 9 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Benchmarking 6DOF Outdoor Visual Localization in Changing Conditions
Sattler, T., Maddern, W., Toft, C., Torii, A., Hammarstrand, L., Stenborg, E., Safari, D., Okutomi, M., Pollefeys, M., Sivic, J., et al. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00897 · Cited by 699 · see citing works
WoodScape: A Multi-Task, Multi-Camera Fisheye Dataset for Autonomous Driving
Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Chennupati, S., Uricar, M., Milz, S., Simon, M., Amende, K., Witt, C., et al. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00940 · Cited by 303 · see citing works
“Pless [42] did pioneering work in deriving a framework for modeling a network of cameras as one, this approach is useful for geometric vision algorithms like visual odometry.”
Background
- Authors
- Pless, R.
- Affiliations
- Washington University in St. Louis (US)
- Corresponding author
- Pless, R.
- ORCID
- Pless, R.
- Venue
- 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings.
- Publisher
- IEEE Comput. Soc
- Published
- 2003-12-22
- Volume
- 2
- Pages
- II-587-93
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2118341165
- Cited by
- 291
- References
- 26
- Citations by year
- 2026: 4 · 2025: 9 · 2024: 9 · 2023: 11 · 2022: 10 · 2021: 11 · 2020: 27 · 2019: 22 · 2018: 12 · 2017: 18 · 2016: 16 · 2015: 19 · 2014: 22 · 2013: 11 · 2012: 4
- FWCI
- 7.13
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
- Physical Sciences › Earth and Planetary Sciences › Geology › 3D Surveying and Cultural Heritage
- Physical Sciences › Engineering › Aerospace Engineering › Robotics and Sensor-Based Localization
- Keywords
- multi-camera systems, structure from motion, epipolar geometry
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
