15.2.10 Fundamental Matrix Computation and Use

Chapter Contents (Back)
Fundamental Matrix. Essential Matrix.

Ganapathy, S.,
Decomposition of Transformation Matrices for Robot Vision,
PRL(2), 1984, pp. 401-412. BibRef 8400
Earlier: CRA84(130-139). BibRef

Luong, Q.T., Faugeras, O.D.,
Self-Calibration of a Moving Camera from Point Correspondences and Fundamental Matrices,
IJCV(22), No. 3, March/April 1997, pp. 261-289.
DOI Link 9706
See also Stability Analysis of the Fundamental Matrix, A. BibRef

Luong, Q.T., Faugeras, O.D.,
An Optimization Framework for Efficient Self-Calibration and Motion Determination,
ICPR94(A:248-252).
IEEE DOI BibRef 9400

Luong, Q.T., and Faugeras, O.D.,
Determining the Fundamental Matrix with Planes: Instability and New Algorithms,
CVPR93(489-494).
IEEE DOI BibRef 9300
Earlier:
Self-Calibration of a Camera Using Multiple Images,
ICPR92(I:9-12).
IEEE DOI Camera calibration for initially uncalibrated stereo images. Other methods are unstable when the points close to planar. BibRef

Faugeras, O.D., Luong, Q.T., Maybank, S.J.,
Camera Self-Calibration: Theory and Experiments,
ECCV92(321-334).
Springer DOI BibRef 9200

Luong, Q.T., Faugeras, O.D.,
The Fundamental Matrix: Theory, Algorithms, and Stability Analysis,
IJCV(17), No. 1, January 1996, pp. 43-75.
Springer DOI
PS File. BibRef 9601
Earlier:
A Stability Analysis of the Fundamental Matrix,
ECCV94(A:577-588).
Springer DOI Fundamental Matrix. See also Self-Calibration of a Moving Camera from Point Correspondences and Fundamental Matrices. BibRef

Luong, Q.T., Deriche, R., Faugeras, O.D., and Papadopoulo, T.,
On Determining the Fundamental Matrix: Analysis of Different Methods and Experimental Results,
INRIATR RR-1894, 1993.
HTML Version. BibRef 9300

Csurka, G., Zeller, C., Zhang, Z.Y., Faugeras, O.D.,
Characterizing the Uncertainty of the Fundamental Matrix,
CVIU(68), No. 1, October 1997, pp. 18-36.
DOI Link 9710
BibRef

Hartley, R.I.,
Kruppa's Equations Derived from the Fundamental Matrix,
PAMI(19), No. 2, February 1997, pp. 133-135.
IEEE DOI 9703
See also Theory of Self-Calibration of a Moving Camera, A. See also Zur Ermittlung eines Objektes aus zwei Perspektiven mit innerer Orientierung. BibRef

Hartley, R.I.[Richard I.],
Minimizing Algebraic Error in Geometric Estimation Problems,
ICCV98(469-476).
IEEE DOI BibRef 9800
And: DARPA97(631-638). BibRef

Torr, P.H.S.[Philip H.S.], Zisserman, A.[Andrew], Maybank, S.J.[Stephen J.],
Robust Detection of Degenerate Configurations while Estimating the Fundamental Matrix,
CVIU(71), No. 3, September 1998, pp. 312-333.
DOI Link BibRef 9809
Earlier:
Robust Detection of Degenerate Configurations for the Fundamental Matrix,
ICCV95(1037-1042).
IEEE DOI BibRef

Bober, M., Georgis, N., Kittler, J.V.,
On Accurate and Robust Estimation of Fundamental Matrix,
CVIU(72), No. 1, October 1998, pp. 39-53.
DOI Link BibRef 9810
Earlier: BMVC96(Poster Session 2). 9608
University of Surrey See also Robust Motion Analysis. BibRef

Brandt, S.S.[Sami S.], Heikkonen, J.[Jukka],
A Bayesian weighting principle for the fundamental matrix estimation,
PRL(21), No. 12, November 2000, pp. 1081-1092. 0011
BibRef
And:
Optimal Method for the Affine F-Matrix and Its Uncertainty Estimation in the Sense of both Noise and Outliers,
ICCV01(II: 166-173).
IEEE DOI 0106
BibRef

Chen, Z.Z.[Ze-Zhi], Wu, C.K.[Cheng-Ke], Shen, P.[Peiyi], Liu, Y.[Yong], Quan, L.[Long],
A robust algorithm to estimate the fundamental matrix,
PRL(21), No. 9, August 2000, pp. 851-861. 0008
See also new image rectification algorithm, A. BibRef

Zhang, Z.Y.[Zheng-You], Xu, G.[Gang],
Unified Theory of Uncalibrated Stereo for Both Perspective and Affine Cameras,
JMIV(9), No. 3, November 1998, pp. 213-229.
DOI Link BibRef 9811
Earlier:
A General expression of the Fundamental Matrix for Both Projective and Affine Cameras,
IJCAI97(1502-1507). See also Motion and Structure from Two Perspective Views: From Essential Parameters to Euclidean Motion Through the Fundamental Matrix. BibRef

Zhang, Z.Y.[Zheng-You], Loop, C.[Charles],
Estimating the Fundamental Matrix by Transforming Image Points in Projective Space,
CVIU(82), No. 2, May 2001, pp. 174-180.
DOI Link 0108
BibRef
Earlier: A2, A1:
Computing Rectifying Homographies for Stereo Vision,
CVPR99(I: 125-131).
IEEE DOI Once you know the mapping, apply the rectification to the images so they line up. BibRef

Zhang, Z.Y.[Zheng-You], Loop, C.[Charles],
System and method for rectifying images of three dimensional objects,
US_Patent6,608,923, Aug 19, 2003
WWW Link. BibRef 0308

Chesi, G.[Graziano], Garulli, A., Vicino, A., Cipolla, R.,
Estimating the Fundamental Matrix via Constrained Least-Squares: A Convex Approach,
PAMI(24), No. 3, March 2002, pp. 397-401.
IEEE DOI 0202
BibRef
Earlier:
On the Estimation of the Fundamental Matrix: A Convex Approach to Constrained Least-Squares,
ECCV00(I: 236-250).
Springer DOI 0003
BibRef

Armangué, X.[Xavier], Salvi, J.[Joaquim],
Overall view regarding fundamental matrix estimation,
IVC(21), No. 2, February 2003, pp. 205-220.
Elsevier DOI 0301
BibRef

Chojnacki, W.[Wojciech], Brooks, M.J.[Michael J.], van den Hengel, A.J.[Anton J.], Gawley, D.[Darren],
A new constrained parameter estimator for computer vision applications,
IVC(22), No. 2, 1 February 2004, pp. 85-91.
Elsevier DOI 0402
BibRef
Earlier: A3, A2, A1, A4:
A New Constrained Parameter Estimator: Experiments in Fundamental Matrix Computation,
BMVC02(Computer Vision Tools). 0208
BibRef
Earlier: A1, A2, A3, A4:
A Fast MLE-Based Method for Estimating the Fundamental Matrix,
ICIP01(II: 189-192).
IEEE DOI 0108
BibRef

Integrate constraints from other than image data, e.g. for calibration. See also 3-D Interpretation of Optical-Flow by Renormalization. See also Determining the Egomotion of an Uncalibrated Camera from Instantaneous Optical Flow. See also Rationalising the Renormalisation Method of Kanatani.

Chojnacki, W.[Wojciech], Hill, R.[Rhys], van den Hengel, A.J.[Anton J.], Brooks, M.J.[Michael J.],
Multi-projective Parameter Estimation for Sets of Homogeneous Matrices,
DICTA09(119-124).
IEEE DOI 0912
BibRef

Chojnacki, W.[Wojciech], Szpak, Z.L.[Zygmunt L.], Brooks, M.J.[Michael J.], van den Hengel, A.J.[Anton J.],
Enforcing consistency constraints in uncalibrated multiple homography estimation using latent variables,
MVA(26), No. 2-3, April 2015, pp. 401-422.
Springer DOI 1504
BibRef
Earlier:
Multiple Homography Estimation with Full Consistency Constraints,
DICTA10(480-485).
IEEE DOI 1012
BibRef

Chojnacki, W.[Wojciech], Szpak, Z.L.[Zygmunt L.],
Full Explicit Consistency Constraints in Uncalibrated Multiple Homography Estimation,
ACCV18(I:659-675).
Springer DOI 1906
BibRef

Szpak, Z.L.[Zygmunt L.], Chojnacki, W.[Wojciech], van den Hengel, A.J.[Anton J.],
Robust multiple homography estimation: An ill-solved problem,
CVPR15(2132-2141)
IEEE DOI 1510
BibRef

Eriksson, A.P.[Anders P.], van den Hengel, A.J.[Anton J.],
Optimization on the manifold of multiple homographies,
Subspace09(242-249).
IEEE DOI 0910
Enforce constraint that homographies for planes lie in a 4D subspace. BibRef

Torr, P.H.S., Fitzgibbon, A.W.,
Invariant Fitting of Two View Geometry,
PAMI(26), No. 5, May 2004, pp. 648-650.
IEEE Abstract. 0404
BibRef
Earlier: A2, A1: BMVC03(xx-yy).
HTML Version. 0409
Extension of See also Fitting Conic Sections to Scattered Data. and See also Fitting Conic Sections to Very Scattered Data: An Iterarive Refinement of the Bookstein Algorithm. for fitting Conics to determine the epipolar geometry to get the Essential Matrix or Fundamental Matrix. BibRef

Seo, J.K.[Jung-Kak], Hong, H.K.[Hyun-Ki], Jho, C.W.[Cheung-Woon], Choi, M.H.[Min-Hyung],
Two quantitative measures of inlier distributions for precise fundamental matrix estimation,
PRL(25), No. 6, 19 April 2004, pp. 733-741.
Elsevier DOI 0405
BibRef

Sagüés, C., Murillo, A.C., Escudero, F., Guerrero, J.J.,
From lines to epipoles through planes in two views,
PR(39), No. 3, March 2006, pp. 384-393.
Elsevier DOI 0601
Fundamental matrix using line matches when planar structure is assumed. BibRef

Zhong, H.X., Pang, Y.J., Feng, Y.P.,
A new approach to estimating fundamental matrix,
IVC(24), No. 1, 1 January 2006, pp. 56-60.
Elsevier DOI 0602
BibRef

Lehmann, S., Bradley, A.P.[Andrew P.], Vaughan, I., Williams, J., Kootsookos, P.J., Clarkson, L.,
Correspondence-Free Determination of the Affine Fundamental Matrix,
PAMI(29), No. 1, January 2007, pp. 82-97.
IEEE DOI 0701
Typically errors in matching dealt with using robust methods. Transmorm to a frequency domain task, match lines in frequency (reasonable model for Orthographic cameras). BibRef

Helmke, U.[Uwe], Hüper, K.[Knut], Lee, P.Y.[Pei Yean], Moore, J.[John],
Essential Matrix Estimation Using Gauss-Newton Iterations on a Manifold,
IJCV(74), No. 2, August 2007, pp. 117-136.
Springer DOI 0705
Estimate the essential matrix from point correspondences between a stereo image pair, assuming that the internal camera parameters are known. BibRef

Kanatani, K.[Kenichi], Sugaya, Y.[Yasuyuki],
High Accuracy Fundamental Matrix Computation and Its Performance Evaluation,
IEICE(E90-D), No. 2, February 2007, pp. 579-585.
DOI Link 0702
BibRef
Earlier: BMVC06(I:217).
PDF File. 0609
See also Statistical Optimization for Geometric Fitting: Theoretical Accuracy Bound and High Order Error Analysis. BibRef

Kanatani, K.[Kenichi], Sugaya, Y.[Yasuyuki],
Compact Fundamental Matrix Computation,
PSIVT09(179-190).
Springer DOI 0901
BibRef
And: A2, A1:
High Accuracy Computation of Rank-Constrained Fundamental Matrix,
BMVC07(xx-yy).
PDF File. 0709
BibRef
And: A2, A1:
Highest Accuracy Fundamental Matrix Computation,
ACCV07(II: 311-321).
Springer DOI 0711
BibRef

Kim, J.S.[Jun-Sik], Kanade, T.[Takeo],
Degeneracy of the Linear Seventeen-Point Algorithm for Generalized Essential Matrix,
JMIV(37), No. 1, May 2010, pp. xx-yy.
Springer DOI 1003
BibRef

Datta, A.[Ankur], Kim, J.S.[Jun-Sik], Kanade, T.[Takeo],
Accurate camera calibration using iterative refinement of control points,
VS09(1201-1208).
IEEE DOI 0910
BibRef

Wu, H.H.P., Chang, S.H.,
Fundamental matrix of planar catadioptric stereo systems,
IET-CV(4), No. 2, June 2010, pp. 85-104.
DOI Link 1007
BibRef

Chen, P.,
Why not use the Levenberg-Marquardt method for fundamental matrix estimation?,
IET-CV(4), No. 4, December 2010, pp. 286-294.
DOI Link 1011
Maybe LM is not as bad as previously thought for computation of fundamental matrix. BibRef

Fathy, M.E.[Mohammed E.], Hussein, A.S.[Ashraf S.], Tolba, M.F.[Mohammed F.],
Fundamental matrix estimation: A study of error criteria,
PRL(32), No. 2, 15 January 2011, pp. 383-391.
Elsevier DOI 1101
BibRef
Earlier:
Simple, Fast and Accurate Estimation of the Fundamental Matrix Using the Extended Eight-point Schemes,
BMVC10(xx-yy).
HTML Version. 1009
Fundamental matrix; Epipolar geometry; Structure and motion BibRef

Zhang, Y.J.[Yong-Jun], Huang, X.[Xu], Hu, X.Y.[Xiang-Yun], Wan, F.Q.[Fang-Qi], Lin, L.[Liwen],
Direct relative orientation with four independent constraints,
PandRS(66), No. 6, November 2011, pp. 809-817.
Elsevier DOI 1112
Direct relative orientation; Essential matrix; Constraint; Accuracy analysis; Least squares adjustment BibRef

de França, J.A.[José Alexandre], Stemmer, M.R.[Marcelo Ricardo], de M. França, M.B.[Maria Bernadete], Piai, J.C.[Juliani Chico],
A new robust algorithmic for multi-camera calibration with a 1D object under general motions without prior knowledge of any camera intrinsic parameter,
PR(45), No. 10, October 2012, pp. 3636-3647.
Elsevier DOI 1206
1D calibration object; Fundamental matrix; Stereo calibration; General rigid motion; Projective geometry BibRef

Steger, C.[Carsten],
Estimating the fundamental matrix under pure translation and radial distortion,
PandRS(74), No. 1, November 2012, pp. 202-217.
Elsevier DOI 1212
Uncalibrated stereo; Fundamental matrix; Radial distortion; Division model; Minimal solver; Overdetermined solver BibRef

Basta, T.[Tayeb],
Is the Fundamental Matrix Really Independent of the Scene Structure?,
IJSIP(7), No. 5, 2014, pp. 13.
PDF File. 1501
BibRef

Bugarin, F.[Florian], Bartoli, A.E.[Adrien E.], Henrion, D.[Didier], Lasserre, J.B.[Jean-Bernard], Orteu, J.J.[Jean-José], Sentenac, T.[Thierry],
Rank-Constrained Fundamental Matrix Estimation by Polynomial Global Optimization Versus the Eight-Point Algorithm,
JMIV(53), No. 1, September 2015, pp. 42-60.
Springer DOI 1505
BibRef

Wang, L., Liu, Z., Zhang, Z.,
Efficient image features selection and weighting for fundamental matrix estimation,
IET-CV(10), No. 1, 2016, pp. 67-78.
DOI Link 1601
cameras BibRef

Moisan, L.[Lionel], Moulon, P.[Pierre], Monasse, P.[Pascal],
Fundamental Matrix of a Stereo Pair, with A Contrario Elimination of Outliers,
IPOL(6), 2016, pp. 89-113.
DOI Link 1605
Code, Fundamental Matrix. See also New A Contrario Approach for the Robust Determination of the Fundamental Matrix, A. See also Automatic Homographic Registration of a Pair of Images, with A Contrario Elimination of Outliers. BibRef

Mohammed, H.M.[Hani Mahmoud], El-Sheimy, N.[Naser],
A Descriptor-less Well-Distributed Feature Matching Method Using Geometrical Constraints and Template Matching,
RS(10), No. 5, 2018, pp. xx-yy.
DOI Link 1806
Feature matching for camera calibration. BibRef

Xiao, C.B.[Chun-Bao], Feng, D.Z.[Da-Zheng], Yuan, M.D.[Ming-Dong],
Soft decision optimization method for robust fundamental matrix estimation,
MVA(30), No. 4, June 2019, pp. 657-669.
Springer DOI 1906
BibRef

Chojnacki, W.[Wojciech], Szpak, Z.L.[Zygmunt L.], Wadenbäck, M.[Mårten],
The equivalence of two definitions of compatible homography matrices,
PRL(135), 2020, pp. 38-43.
Elsevier DOI 2006
Multiple homographies, Homography matrix, Fundamental matrix, Latent variable BibRef

Miraldo, P.[Pedro], Cardoso, J.R.[João R.],
On the Generalized Essential Matrix Correction: An Efficient Solution to the Problem and Its Applications,
JMIV(62), No. 8, October 2020, pp. xx-yy.
WWW Link. 2009
BibRef


Geifman, A., Kasten, Y., Galun, M., Basri, R.,
Averaging Essential and Fundamental Matrices in Collinear Camera Settings,
CVPR20(6020-6029)
IEEE DOI 2008
Cameras, Tensile stress, Symmetric matrices, Eigenvalues and eigenfunctions, Bundle adjustment, Optimization BibRef

Zhao, J., Xu, W., Kneip, L.,
A Certifiably Globally Optimal Solution to Generalized Essential Matrix Estimation,
CVPR20(12031-12040)
IEEE DOI 2008
Cameras, Optimization, Pose estimation, Geometry, Eigenvalues and eigenfunctions BibRef

Kasten, Y., Geifman, A., Galun, M., Basri, R.,
Algebraic Characterization of Essential Matrices and Their Averaging in Multiview Settings,
ICCV19(5894-5902)
IEEE DOI 2004
calibration, cameras, image reconstruction, matrix algebra, optimisation, algebraic characterization, multiview settings, Eigenvalues and eigenfunctions BibRef

Wuerfl, T., Aichert, A., Maass, N., Dennerlein, F., Maier, A.,
Estimating the Fundamental Matrix Without Point Correspondences With Application to Transmission Imaging,
ICCV19(1072-1081)
IEEE DOI 2004
calibration, cameras, computer vision, computerised tomography, feature extraction, image matching, image reconstruction, Estimation BibRef

Poursaeed, O.[Omid], Yang, G.[Guandao], Prakash, A.[Aditya], Fang, Q.[Qiuren], Jiang, H.Q.[Han-Qing], Hariharan, B.[Bharath], Belongie, S.[Serge],
Deep Fundamental Matrix Estimation Without Correspondences,
DeepLearn-G18(III:485-497).
Springer DOI 1905
BibRef

Barath, D.,
Five-Point Fundamental Matrix Estimation for Uncalibrated Cameras,
CVPR18(235-243)
IEEE DOI 1812
Mathematical model, Estimation, Cameras, Transmission line matrix methods, Linear systems, Detectors BibRef

Trager, M.[Matthew], Osserman, B.[Brian], Ponce, J.[Jean],
On the Solvability of Viewing Graphs,
ECCV18(XVI: 335-350).
Springer DOI 1810
How fundamental matrices of pair of cameras interact. BibRef

Ranftl, R.[René], Koltun, V.[Vladlen],
Deep Fundamental Matrix Estimation,
ECCV18(I: 292-309).
Springer DOI 1810
BibRef

Sengupta, S., Amir, T., Galun, M., Goldstein, T., Jacobs, D.W., Singer, A., Basri, R.,
A New Rank Constraint on Multi-view Fundamental Matrices, and Its Application to Camera Location Recovery,
CVPR17(2413-2421)
IEEE DOI 1711
Calibration, Cameras, Estimation, Jacobian matrices, Optimization, Stacking, Symmetric, matrices BibRef

Zhou, Y., Kneip, L., Li, H.,
A Revisit of Methods for Determining the Fundamental Matrix with Planes,
DICTA15(1-7)
IEEE DOI 1603
image processing BibRef

Barragan, D.[Daniel], Trujillo, M.[Maria], Cabezas, I.[Ivan],
An EA-Based Method for Estimating the Fundamental Matrix,
CIARP15(228-235).
Springer DOI 1511
BibRef

Zhang, M.[Ming], Wang, G.H.[Guang-Hui], Chao, H.[Haiyang], Wu, F.C.[Fu-Chao],
Fast and Robust Algorithm for Fundamental Matrix Estimation,
ICIAR15(316-322).
Springer DOI 1507
BibRef

Mirabdollah, M.H.[M. Hossein], Mertsching, B.[Bärbel],
On the Second Order Statistics of Essential Matrix Elements,
GCPR14(547-557).
Springer DOI 1411
BibRef

Fathy, M.[Mohammed], Rotkowitz, M.[Michael],
Essential Matrix Estimation Using Adaptive Penalty Formulations,
BMVC14(xx-yy).
HTML Version. 1410
BibRef

Yang, J.[Jiaolong], Li, H.D.[Hong-Dong], Jia, Y.D.[Yun-De],
Optimal Essential Matrix Estimation via Inlier-Set Maximization,
ECCV14(I: 111-126).
Springer DOI 1408
BibRef

Okutani, R., Kuroki, Y.,
An estimation of the fundamental matrix using hybrid statistics,
VCIP13(1-6)
IEEE DOI 1402
image representation BibRef

Espuny, F.[Ferran], Monasse, P.[Pascal],
Singular Vector Methods for Fundamental Matrix Computation,
PSIVT13(290-301).
Springer DOI 1402
BibRef

Espuny, F.[Ferran], Monasse, P.[Pascal], Moisan, L.[Lionel],
A New A Contrario Approach for the Robust Determination of the Fundamental Matrix,
PSIVTWS13(181-192).
Springer DOI 1402
Code: See also Fundamental Matrix of a Stereo Pair, with A Contrario Elimination of Outliers. BibRef

Li, Y.[Yi], Velipasalar, S., Gursoy, M.C.,
An improved evolutionary algorithm for fundamental matrix estimation,
AVSS13(226-231)
IEEE DOI 1311
estimation theory BibRef

Zheng, Y.Q.[Yin-Qiang], Sugimoto, S.[Shigeki], Okutomi, M.[Masatoshi],
A Practical Rank-Constrained Eight-Point Algorithm for Fundamental Matrix Estimation,
CVPR13(1546-1553)
IEEE DOI 1309
BibRef

Guerra-Filho, G.[Gutemberg],
Discretization effects in the fundamental matrix computation,
ICIP12(3025-3028).
IEEE DOI 1302
BibRef

Brito, J.H.[José Henrique], Zach, C.[Christopher], Koeser, K.[Kevin], Ferreira, M.[Manuel], Pollefeys, M.[Marc],
One-sided Radial-Fundamental Matrix Estimation,
BMVC12(96).
DOI Link 1301
BibRef

Carro, A.I.[Alberto Irurueta], Morros, J.R.[Josep Ramon],
Promeds: An adaptive robust fundamental matrix estimation approach,
3DTV12(1-4).
IEEE DOI 1212
BibRef

Chan, K.H.[Kai-Hsuan], Wu, Y.L.[Yi-Leh], Tang, C.Y.[Cheng-Yuan], Hor, M.K.[Maw-Kae],
Robust Orthogonal Particle Swarm Optimization for estimating the fundamental matrix,
VCIP11(1-4).
IEEE DOI 1201
BibRef

Tegolo, D.[Domenico], Bellavia, F.[Fabio],
noRANSAC for fundamental matrix estimation,
BMVC11(xx-yy).
HTML Version. 1110
BibRef

Zheng, Y.Q.[Yin-Qiang], Sugimoto, S.[Shigeki], Sato, I.[Imari], Okutomi, M.[Masatoshi],
A General and Simple Method for Camera Pose and Focal Length Determination,
CVPR14(430-437)
IEEE DOI 1409
BibRef

Zheng, Y.Q.[Yin-Qiang], Sugimoto, S.[Shigeki], Yan, S.C.[Shui-Cheng], Okutomi, M.[Masatoshi],
Generalizing Wiberg algorithm for rigid and nonrigid factorizations with missing components and metric constraints,
CVPR12(2010-2017).
IEEE DOI 1208
BibRef

Zheng, Y.Q.[Yin-Qiang], Sugimoto, S.[Shigeki], Okutomi, M.[Masatoshi],
A branch and contract algorithm for globally optimal fundamental matrix estimation,
CVPR11(2953-2960).
IEEE DOI 1106
BibRef

Zhou, H.Y.[Hui-Yu], Schaefer, G.[Gerald],
Robust estimation of the fundamental matrix,
ICIP10(4233-4236).
IEEE DOI 1009
BibRef

Fakih, A.H., Zelek, J.S.[John S.],
Determination of the essential matrix using discrete and differential matching constraints,
CIIP09(110-115).
IEEE DOI 0903
BibRef

Skarbek, W.[Wladyslaw], Tomaszewski, M.[Michal],
Epipolar Angular Factorisation of Essential Matrix for Camera Pose Calibration,
MIRAGE09(401-412).
Springer DOI 0905
BibRef

Sukumar, S.R.[Sreenivas R.], Bozdogan, H.[Hamparsum], Page, D.L.[David L.], Koschan, A.F.[Andreas F.], Abidi, M.A.[Mongi A.],
On handling uncertainty in the fundamental matrix for scene and motion adaptive pose recovery,
CVPR08(1-8).
IEEE DOI 0806
BibRef

Den Hollander, R., Hanjalic, A.,
A Combined RANSAC-Hough Transform Algorithm for Fundamental Matrix Estimation,
BMVC07(xx-yy).
PDF File. 0709
BibRef

Sur, F.[Frederic], Noury, N.[Nicolas], Berger, M.O.[Marie-Odile],
Computing the Uncertainty of the 8 point Algorithm for Fundamental Matrix Estimation,
BMVC08(xx-yy).
PDF File. 0809
BibRef
Earlier: A2, A1, A3:
Fundamental Matrix Estimation Without Prior Match,
ICIP07(I: 513-516).
IEEE DOI 0709
BibRef

Sheikh, Y.[Yaser], Hakeem, A.[Asaad], Shah, M.[Mubarak],
On the Direct Estimation of the Fundamental Matrix,
CVPR07(1-7).
IEEE DOI 0706
BibRef

Fan, X.D.[Xiao-Dong], Vidal, R.[René],
The Space of Multibody Fundamental Matrices: Rank, Geometry and Projection,
WDV06(1-17).
Springer DOI 0705
BibRef

Levi, N., Werman, M.,
The viewing graph,
CVPR03(I: 518-522).
IEEE DOI 0307
Given N views, and some inter-view matricies, which others can we compute. BibRef

Li, Q.[Qi], Li, T.[Tao], Zhu, S.H.[Sheng-Huo], Kambhamettu, C.,
How well can wavelet denoising improve the accuracy of computing fundamental matrices?,
Motion02(247-252).
IEEE DOI 0303
BibRef

Salvi, J., Armangué, X., Pagés, J.,
A Survey Addressing the Fundamental Matrix Estimation Problem,
ICIP01(II: 209-212).
IEEE DOI 0108
Survey, Fundamental Matrix. BibRef

Lourakis, M.I.A.[Manolis I.A.], and Deriche, R.[Rachid],
Camera Self-Calibration Using the Singular Value Decomposition of the Fundamental Matrix,
ACCV00(I: 403-408). SVD
PS File. 0001
BibRef
And:
Camera Self-Calibration Using the Singular Value Decomposition of the Fundamental Matrix: From Point Correspondences to 3D Measurements,
INRIARR-3748, August 1999.
HTML Version.
PS File.
PDF File. BibRef

Lourakis, M.I.A.[Manolis I.A.], and Deriche, R.[Rachid],
Camera Self-Calibration Using the Kruppa Equations and the SVD of the Fundamental Matrix: The Case of Varying Intrinsic Parameters,
INRIARR-3911, March 2000.
HTML Version.
PS File.
PDF File. BibRef 0003

Isgrò, F.[Francesco], Trucco, E.[Emanuele],
A General Rank-2 Parameterization of the Fundamental Matrix,
ICPR00(Vol I: 868-871).
IEEE DOI 0009
BibRef

Li, F., Brady, J.M., Wiles, C.,
Fast Computation of the Fundamental Matrix for an Active Stereo Vision System,
ECCV96(I:157-166).
Springer DOI BibRef 9600

Chapter on Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following continues in
Camera Calibration, Lens Distortion, Aberration, Radial Distortion, Internal Parameters .


Last update:Sep 24, 2020 at 19:44:22