13.7.1 RANSAC Matching Issues, Design, Evaluation, Related Sample Matching

Chapter Contents (Back)
RANSAC.

Fischler, M.A., and Bolles, R.C.,
Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography,
CACM(24), No. 6, June 1981, pp. 381-395. BibRef 8106
And: RCV87(726-740). BibRef
Earlier: DARPA80(71-88). BibRef
And: SRI-TN-213, March 1980.
WWW Link. RANSAC. Robust Technique. BibRef
And:
A RANSAC-Based Approach to Model Fitting and Its Application to Finding Cylinders in Range Data,
IJCAI81(637-643). RANSAC algorithm for matching data points to the model. This allows error points to be eliminated and thus ignored - find a match that a majority of the points are happy with. BibRef

Bolles, R.C.,
Robust Feature Matching Through Maximal Cliques,
SPIE(182), Imaging Applications for Automated Industrial Inspection and Assembly, 1979, pp. 140-149. BibRef 7900

Roth, G.[Gerhard], and Levine, M.D.[Martin D.],
Minimal Subset Random Sampling for Pose Determination and Refinement,
AMV Strategies921992, pp. 1-21. RANSAC.
See also Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography. RANSAC is good and can be generalized and extended. BibRef 9200

Matas, J.G.[Jirí G.], Chum, O.[Ondrej],
Randomized RANSAC with Td,d test,
IVC(22), No. 10, 1 September 2004, pp. 837-842.
Elsevier DOI 0409
BibRef
Earlier:
Randomized RANSAC with T(d,d) test,
BMVC02(Computer Vision Tools). 0208
Time savings from evaluating only a part of the points. BibRef

Chum, O.[Ondrej], Matas, J.G.[Jirí G.],
Optimal Randomized RANSAC,
PAMI(30), No. 8, August 2008, pp. 1472-1482.
IEEE DOI 0806
BibRef
Earlier:
Geometric Hashing with Local Affine Frames,
CVPR06(I: 879-884).
IEEE DOI 0606
BibRef
Earlier:
Matching with PROSAC: Progressive Sample Consensus,
CVPR05(I: 220-226).
IEEE DOI 0507
BibRef
And: A2, A1:
Randomized RANSAC with Sequential Probability Ratio Test,
ICCV05(II: 1727-1732).
IEEE DOI 0510
BibRef

Mikulik, A.[Andrej], Matas, J.G.[Jiri G.], Perdoch, M.[Michal], Chum, O.[Ondrej],
Construction of Precise Local Affine Frames,
ICPR10(3565-3569).
IEEE DOI 1008
BibRef

Chum, O.[Ondrej], Matas, J.G.[Jiri G.], Kittler, J.V.[Josef V.],
Locally Optimized RANSAC,
DAGM03(236-243).
Springer DOI 0310
BibRef

Chum, O.[Ondrej], Matas, J.G.[Jirí G.],
Planar Affine Rectification from Change of Scale,
ACCV10(IV: 347-360).
Springer DOI 1011
BibRef

Nistér, D.[David],
Preemptive RANSAC for live structure and motion estimation,
MVA(16), No. 5, December 2005, pp. 321-329.
Springer DOI 0601
BibRef
Earlier: ICCV03(199-206).
IEEE DOI 0311
BibRef

Cheng, C.M.[Chia-Ming], Lai, S.H.[Shang-Hong],
A consensus sampling technique for fast and robust model fitting,
PR(42), No. 7, July 2009, pp. 1318-1329.
Elsevier DOI 0903
RANSAC; Robust estimation; Model fitting; Fundamental matrix estimation BibRef

Scherer-Negenborn, N.[Norbert], Schaefer, R.[Rolf],
Model Fitting with Sufficient Random Sample Coverage,
IJCV(89), No. 1, August 2010, pp. xx-yy.
Springer DOI 1004
RANSAC. Compute how many iterations should really be needed. BibRef

Toldo, R.[Roberto], Fusiello, A.[Andrea],
Real-time Incremental J-Linkage for Robust Multiple Structures Estimation,
3DPVT10(xx-yy).
WWW Link. 1005
BibRef
Earlier:
Automatic Estimation of the Inlier Threshold in Robust Multiple Structures Fitting,
CIAP09(123-131).
Springer DOI 0909
BibRef
Earlier:
Robust Multiple Structures Estimation with J-Linkage,
ECCV08(I: 537-547).
Springer DOI 0810
Deal with multiple instances of the same structure, which complicate RANSAC operation. BibRef

Raguram, R.[Rahul], Chum, O.[Ondrej], Pollefeys, M.[Marc], Matas, J.G.[Jiri G.], Frahm, J.M.[Jan-Michael],
USAC: A Universal Framework for Random Sample Consensus,
PAMI(35), No. 8, 2013, pp. 2022-2038.
IEEE DOI 1307
RANSAC; robust estimation BibRef

Hassner, T.[Tal], Assif, L.[Liav], Wolf, L.B.[Lior B.],
When standard RANSAC is not enough: Cross-media visual matching with hypothesis relevancy,
MVA(25), No. 4, May 2014, pp. 971-983.
WWW Link. 1404
BibRef

Imre, E.[Evren], Hilton, A.[Adrian],
Order Statistics of RANSAC and Their Practical Application,
IJCV(111), No. 3, February 2015, pp. 276-297.
WWW Link. 1503
BibRef

Djurovic, I.,
A WD-RANSAC Instantaneous Frequency Estimator,
SPLetters(23), No. 5, May 2016, pp. 757-761.
IEEE DOI 1604
Complexity theory BibRef

Djurovic, I.,
QML-RANSAC Instantaneous Frequency Estimator for Overlapping Multicomponent Signals in the Time-Frequency Plane,
SPLetters(25), No. 3, March 2018, pp. 447-451.
IEEE DOI 1802
Frequency estimation, Frequency modulation, Maximum likelihood estimation, Signal processing algorithms, short-time Fourier transform (STFT) BibRef

Wang, Y.[Yue], Zheng, J.[Jin], Xu, Q.Z.[Qi-Zhi], Li, B.[Bo], Hu, H.M.[Hai-Miao],
An improved RANSAC based on the scale variation homogeneity,
JVCIR(40, Part B), No. 1, 2016, pp. 751-764.
Elsevier DOI 1610
Scale variation homogeneity BibRef

Li, Y.M.[Ying-Mao], Gans, N.R.[Nicholas R.],
Predictive RANSAC: Effective model fitting and tracking approach under heavy noise and outliers,
CVIU(161), No. 1, 2017, pp. 99-113.
Elsevier DOI 1708
Robust estimation BibRef

Le, V.H.[Van-Hung], Vu, H.[Hai], Nguyen, T.T.[Thuy Thi], Le, T.L.[Thi-Lan], Tran, T.H.[Thanh-Hai],
Acquiring qualified samples for RANSAC using geometrical constraints,
PRL(102), 2018, pp. 58-66.
Elsevier DOI 1802
RANSAC, RANSAC family, Sampling method, Geometrical analysis BibRef

Tran, N., Le Tan, D., Doan, A., Do, T., Bui, T., Tan, M., Cheung, N.,
On-Device Scalable Image-Based Localization via Prioritized Cascade Search and Fast One-Many RANSAC,
IP(28), No. 4, April 2019, pp. 1675-1690.
IEEE DOI 1901
feature extraction, image retrieval, pose estimation, search problems, extensive city regions, mobile devices, RANSAC BibRef

Sangappa, H.K.[Hemanth Kumar], Ramakrishnan, K.R.,
A probabilistic analysis of a common RANSAC heuristic,
MVA(30), No. 1, February 2019, pp. 71-89.
WWW Link. 1904
BibRef

Zhou, H.Y.[Hao-Yin], Zhang, T.[Tao], Jagadeesan, J.[Jayender],
Re-weighting and 1-Point RANSAC-Based PnnP Solution to Handle Outliers,
PAMI(41), No. 12, December 2019, pp. 3022-3033.
IEEE DOI 1911
Cameras, Iterative methods, Linear programming, Time complexity, Pose estimation, robustness to outliers BibRef

Xiang, H.Y.[Heng-Yong], Zhou, L.[Li], Ba, X.H.[Xiao-Hui], Chen, J.[Jie],
Matching with GUISAC-Guided Sample Consensus,
IEICE(E104-D), No. 2, February 2021, pp. 346-349.
WWW Link. 2102
BibRef

Riu, C.[Clément], Nozick, V.[Vincent], Monasse, P.[Pascal],
Automatic RANSAC by Likelihood Maximization,
IPOL(12), 2022, pp. 27-49.
DOI Link 2204
Code, RANSAC.
See also Likelihood-Ratio Test and Efficient Robust Estimation, The. BibRef

Barath, D.[Daniel], Matas, J.G.[Jiri G.],
Graph-Cut RANSAC: Local Optimization on Spatially Coherent Structures,
PAMI(44), No. 9, September 2022, pp. 4961-4974.
IEEE DOI 2208
BibRef
Earlier:
Graph-Cut RANSAC,
CVPR18(6733-6741)
IEEE DOI 1812
Spatial coherence, Optimization, Data models, Estimation, Standards, Labeling, Computational modeling, Robust model estimation, RANSAC, graph-cut. Optimization, Spatial coherence, Standards, Minimization. BibRef

Chung, K.L.[Kuo-Liang], Tseng, Y.C.[Ya-Chi], Chen, H.Y.[Hsuan-Ying],
A Novel and Effective Cooperative RANSAC Image Matching Method Using Geometry Histogram-Based Constructed Reduced Correspondence Set,
RS(14), No. 14, 2022, pp. xx-yy.
DOI Link 2208
BibRef


Wei, T.[Tong], Matas, J.[Jirí], Barath, D.[Daniel],
Adaptive Reordering Sampler with Neurally Guided MAGSAC,
ICCV23(18117-18127)
IEEE DOI Code:
WWW Link. 2401
BibRef

Wei, T.[Tong], Patel, Y.[Yash], Shekhovtsov, A.[Alexander], Matas, J.[Jirí], Barath, D.[Daniel],
Generalized Differentiable RANSAC,
ICCV23(17603-17614)
IEEE DOI Code:
WWW Link. 2401
BibRef

Piedade, V.[Valter], Miraldo, P.[Pedro],
BANSAC: A dynamic BAyesian Network for adaptive SAmple Consensus,
ICCV23(3715-3724)
IEEE DOI Code:
WWW Link. 2401
BibRef

Cavalli, L.[Luca], Pollefeys, M.[Marc], Barath, D.[Daniel],
NeFSAC: Neurally Filtered Minimal Samples,
ECCV22(XXXII:351-366).
Springer DOI 2211

WWW Link. BibRef

Barath, D.[Daniel], Valasek, G.[Gábor],
Space-Partitioning RANSAC,
ECCV22(XXXII:721-737).
Springer DOI 2211
BibRef

Barath, D.[Daniel], Cavalli, L.[Luca], Pollefeys, M.[Marc],
Learning to Find Good Models in RANSAC,
CVPR22(15723-15732)
IEEE DOI 2210
Geometry, Adaptation models, Filtering, Pose estimation, Pipelines, 3D from multi-view and sensors, Low-level vision BibRef

Le, H., Zach, C.,
A Graduated Filter Method for Large Scale Robust Estimation,
CVPR20(5558-5567)
IEEE DOI 2008
Robustness, Optimization, Kernel, Estimation, Schedules, Task analysis, Parameter estimation BibRef

Cohen, A., Zach, C.,
The Likelihood-Ratio Test and Efficient Robust Estimation,
ICCV15(2282-2290)
IEEE DOI 1602
RANSAC Computational modeling
See also Automatic RANSAC by Likelihood Maximization. BibRef

Elashry, A., Sluis, B., Toth, C.,
Improving Ransac Feature Matching Based on Geometric Relation,
ISPRS21(B2-2021: 321-327).
DOI Link 2201
BibRef

Shen, X.[Xi], Darmon, F.[François], Efros, A.A.[Alexei A.], Aubry, M.[Mathieu],
RANSAC-flow: Generic Two-stage Image Alignment,
ECCV20(IV:618-637).
Springer DOI 2011
BibRef

Kluger, F., Brachmann, E., Ackermann, H., Rother, C., Yang, M.Y., Rosenhahn, B.,
CONSAC: Robust Multi-Model Fitting by Conditional Sample Consensus,
CVPR20(4633-4642)
IEEE DOI 2008
Estimation, Robustness, Data models, Neural networks, Computational modeling, Task analysis BibRef

Brachmann, E., Rother, C.,
Neural-Guided RANSAC: Learning Where to Sample Model Hypotheses,
ICCV19(4321-4330)
IEEE DOI 2004
computational geometry, feature extraction, learning (artificial intelligence), neural nets, optimisation, Cameras BibRef

Korman, S., Litman, R.,
Latent RANSAC,
CVPR18(6693-6702)
IEEE DOI 1812
Estimation, Pipelines, Transforms, Cameras, Computational modeling BibRef

Zhang, S.T.[Song-Tao], Chao, L.[Li], Li, L.Q.[Li-Qing],
An improved method for eliminating false matches,
ICIVC17(133-137)
IEEE DOI 1708
Bidirectional control, Feature extraction, Filtering algorithms, Image matching, Matched filters, BF, ORB, RANSAC, bi-direction matching, distance-ratio criterion, eliminating false matches BibRef

Litman, R.[Roee], Korman, S.[Simon], Bronstein, A.M.[Alex M.], Avidan, S.[Shai],
Inverting RANSAC: Global model detection via inlier rate estimation,
CVPR15(5243-5251)
IEEE DOI 1510
BibRef

Fragoso, V.[Victor], Sen, P.[Pradeep], Rodriguez, S.[Sergio], Turk, M.[Matthew],
EVSAC: Accelerating Hypotheses Generation by Modeling Matching Scores with Extreme Value Theory,
ICCV13(2472-2479)
IEEE DOI 1403
extreme value theory; ransac; robust estimation BibRef

Lebeda, K.[Karel], Matas, J.G.[Jirí G.], Chum, O.[Ondrej],
Fixing the Locally Optimized RANSAC,
BMVC12(95).
DOI Link 1301
BibRef

Otte, S.[Sebastian], Schwanecke, U.[Ulrich], Zell, A.[Andreas],
ANTSAC: A Generic RANSAC Variant Using Principles of Ant Colony Algorithms,
ICPR14(3558-3563)
IEEE DOI 1412
Algorithm design and analysis BibRef

Distante, C.[Cosimo], Indiveri, G.[Giovanni],
RANSAC-LEL: An optimized version with least entropy like estimators,
ICIP11(1425-1428).
IEEE DOI 1201
BibRef

Monnin, D.[David], Bieber, E.[Etienne], Schmitt, G.[Gwenaél], Schneider, A.[Armin],
An Effective Rigidity Constraint for Improving RANSAC in Homography Estimation,
ACIVS10(II: 203-214).
Springer DOI 1012
BibRef

Meler, A.[Antoine], Decrouez, M.[Marion], Crowley, J.L.[James L.],
Betasac: A New Conditional Sampling for RANSAC,
BMVC10(xx-yy).
HTML Version. 1009
BibRef

Sattler, T.[Torsten], Leibe, B.[Bastian], Kobbelt, L.[Leif],
SCRAMSAC: Improving RANSAC's efficiency with a spatial consistency filter,
ICCV09(2090-2097).
IEEE DOI 0909
BibRef

Lara-Alvarez, C.[Carlos], Romero, L.[Leonardo], Flores, J.F.[Juan F.], Gomez, C.[Cuauhtemoc],
A Simple Sample Consensus Algorithm to Find Multiple Models,
CIARP09(918-925).
Springer DOI 0911
MuSAC alternative to RANSAC BibRef

Zhang, L.[Liang], Wang, D.[Demin],
LLN-based Model-Driven Validation of Data Points for Random Sample Consensus Methods,
ICPR10(3436-3439).
IEEE DOI 1008
BibRef

Zhang, L.[Liang], Rastgar, H.[Houman], Wang, D.[Demin], Vincent, A.[André],
Maximum Likelihood Estimation Sample Consensus with Validation of Individual Correspondences,
ISVC09(I: 447-456).
Springer DOI 0911
BibRef

He, Z.C.[Zhou-Can], Wang, Q.[Qing], Yang, H.[Heng],
TOCSAC: TOpology Constraint SAmple Consensus for Fast and Reliable Feature Correspondence,
ISVC09(II: 608-618).
Springer DOI 0911
BibRef

Choi, S.[Sunglok], Kim, T.[Taemin], Yu, W.[Wonpil],
Performance Evaluation of RANSAC Family,
BMVC09(xx-yy).
PDF File. 0909
Evaluation, RANSAC. RANSAC. BibRef

Choi, J.M.[Jong-Moo], Medioni, G.[Gerard],
StaRSaC: Stable random sample consensus for parameter estimation,
CVPR09(675-682).
IEEE DOI 0906
BibRef

Raguram, R.[Rahul], Frahm, J.M.[Jan-Michael],
RECON: Scale-adaptive robust estimation via Residual Consensus,
ICCV11(1299-1306).
IEEE DOI 1201
Robust method for noisy data. BibRef

Raguram, R.[Rahul], Frahm, J.M.[Jan-Michael], Pollefeys, M.[Marc],
Exploiting uncertainty in random sample consensus,
ICCV09(2074-2081).
IEEE DOI 0909
BibRef
Earlier:
A Comparative Analysis of RANSAC Techniques Leading to Adaptive Real-Time Random Sample Consensus,
ECCV08(II: 500-513).
Springer DOI 0810
BibRef

Marquez-Neila, P.[Pablo], Miro, J.G.[Jacobo Garcia], Buenaposada, J.M.[Jose M.], Baumela, L.[Luis],
Improving RANSAC for fast landmark recognition,
VisLoc08(1-8).
IEEE DOI 0806
BibRef

Zhang, W.[Wei], Kosecka, J.[Jana],
Generalized RANSAC Framework for Relaxed Correspondence Problems,
3DPVT06(854-860).
IEEE DOI 0606
BibRef

Rodehorst, V.[Volker], Hellwich, O.[Olaf],
Genetic Algorithm SAmple Consensus (GASAC): A Parallel Strategy for Robust Parameter Estimation,
RANSAC06(103).
IEEE DOI 0609
BibRef

Subbarao, R.[Raghav], Meer, P.[Peter],
Beyond RANSAC: User Independent Robust Regression,
RANSAC06(101).
IEEE DOI 0609
BibRef

Frahm, J.M.[Jan-Michael], Pollefeys, M.[Marc],
RANSAC for (Quasi-)Degenerate data (QDEGSAC),
CVPR06(I: 453-460).
IEEE DOI 0606
BibRef

Capel, D.P.,
An Effective Bail-out Test for RANSAC Consensus Scoring,
BMVC05(xx-yy).
HTML Version. 0509
BibRef

Zuliani, M., Kenney, C.S., Manjunath, B.S.,
The Multiransac Algorithm and its Application to Detect Planar Homographies,
ICIP05(III: 153-156).
IEEE DOI 0512
BibRef

Rozenfeld, S.[Stas], Shimshoni, I.[Ilan],
The Modified pbM-Estimator Method and a Runtime Analysis Technique for the RANSAC Family,
CVPR05(I: 1113-1120).
IEEE DOI 0507

See also Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography. BibRef

Chapter on Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants continues in
String Matching, Text Matching .


Last update:Mar 16, 2024 at 20:36:19