Randomized RANSAC with T, test
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?
RANSAC works better than LS method because RANSAC only needs to select a set of inliers to get a good model, instead of selecting all the data points.
“RANSAC works better than LS method because RANSAC only needs to select a set of inliers to get a good model, instead of selecting all the data points.”
Cites
Multiple View Geometry in Computer Vision
Hartley, R., & Zisserman, A. (2004) · doi:10.1017/cbo9780511811685 · Cited by 21,070 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Grauman, K., & Leibe, B. (2011) · Synthesis Lectures on Artificial Intelligence and Machine Learning · doi:10.2200/s00332ed1v01y201103aim011 · Cited by 126 · see citing works
Liu, X., Li, T., Fan, X., & Chen, Z. (2019) · Sensors · doi:10.3390/s19061477 · Cited by 8 · see citing works
“The RANSAC algorithm iteratively repeats the above steps until the obtained consensus set in a certain iteration has enough inliers [26].”
Method
- Authors
- Matas, J., & Chum, O.
- Affiliations
- University of Surrey (GB)
- Czech Technical University in Prague (CZ)
- Corresponding author
- Chum, O
- Venue
- Image and Vision Computing
- Publisher
- Elsevier BV
- Published
- 2004-09
- Volume
- 22
- Issue
- 10
- Pages
- 837-842
- ISSN
- 0262-8856 (ISSN-L)
- OpenAlex
- W2129363926
- Cited by
- 281
- References
- 1
- Citations by year
- 2026: 4 · 2025: 7 · 2024: 11 · 2023: 10 · 2022: 11 · 2021: 19 · 2020: 9 · 2019: 10 · 2018: 11 · 2017: 10 · 2016: 11 · 2015: 14 · 2014: 11 · 2013: 14 · 2012: 20
- FWCI
- 11.31
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Image and Vision Computing (publishedVersion)
- Funders
- European Commission
- Grantová Agentura České Republiky
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Object Detection Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Statistical Methods and Models
- Keywords
- RANSAC, robust estimation, outlier removal, hypothesis evaluation, hypothesis testing, computational efficiency, model parameter estimation
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 ›
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