10.1.3.1 EpiPolar Analysis

Giblin, P.J.[Peter J.], Weiss, R.S.[Richard S.],
Epipolar Curves on Surfaces,
IVC(13), No. 1, February 1995, pp. 33-44.
Elsevier DOI BibRef 9502
Earlier: ARPA94(II:1481-1485). BibRef
And:
Epipolar Fields on Surfaces,
ECCV94(A:14-23).
Springer DOI BibRef
Earlier:
Reconstructions of Surfaces from Profiles,
ICCV87(136-144). BibRef
And: DARPA87(900-908). BibRef

Papadimitriou, D.V., Dennis, T.J.,
Epipolar Line Estimation and Rectification for Stereo Image Pairs,
IP(5), No. 4, April 1996, pp. 672-676.
IEEE DOI 9605
BibRef

Xu, G.[Gang], Zhang, Z.Y.[Zheng-You],
Epipolar Geometry in Stereo, Motion, and Object Recognition: A Unified Approach,
KluwerSeptember 1996. ISBN 0-7923-4199-6.
WWW Link. BibRef 9609

Xu, G.[Gang],
A Unified Approach to Image Matching and Segmentation in Stereo, Motion, and Object Recognition via Recovery of Epipolar Geometry,
Videre(1), No. 1, 1997, pp. 22-55. By recovering epipolar geometry, the other problems are easier. Abstract:
HTML Version. Full paper:
PDF File. BibRef 9700

Tomasi, C.[Carlo], and Manduchi, R.[Roberto],
Stereo Matching as a Nearest-Neighbor Problem,
PAMI(20), No. 3, March 1998, pp. 333-340.
IEEE DOI 9805
Represent images using intrinsic curves to convert match from search to nearest neighbor. Intrinsic curves are the paths of a set of image descriptors in a scanline. E.g. in 3-D plot postion (X), low-pass, derivative. Project onto the X=0 plane. This is an intrinsic curve. BibRef

Tomasi, C., Manduchi, R.,
Stereo without Search,
ECCV96(I:452-465).
Springer DOI Scanline method, using curve representing the scan line. BibRef 9600

Zhang, Z.Y.,
Determining The Epipolar Geometry And Its Uncertainty: A Review,
IJCV(27), No. 2, March 1998, pp. 161-195.
DOI Link 9805
Early version:
PS File. BibRef

Birchfield, S.T.[Stan T.], Tomasi, C.[Carlo],
A Pixel Dissimilarity Measure That Is Insensitive to Image Sampling,
PAMI(20), No. 4, April 1998, pp. 401-406.
IEEE DOI 9806
For stereo matching, how to compare two pixels -- used for comparing epiploar lines. BibRef

Chai, J.X.[Jin-Xiang], Ma, S.D.[Song De],
Robust epipolar geometry estimation using genetic algorithm,
PRL(19), No. 9, 31 July 1998, pp. 829-838. BibRef 9807

Boufama, B.S., Mohr, R.,
A Stable and Accurate Algorithm for Computing Epipolar Geometry,
PRAI(12), No. 6, September 1998, pp. 817. BibRef 9809

Boufama, B.S.[Boubakeur-Seddik], Mohr, R.[Roger],
Epipole and Fundamental Matrix Estimation Using Virtual Parallax,
ICCV95(1030-1036).
IEEE DOI BibRef 9500

Basri, R.[Ronen], Rivlin, E.[Ehud], Shimshoni, I.[Ilan],
Visual Homing: Surfing on the Epipoles,
IJCV(33), No. 2, September 1999, pp. 117-137.
DOI Link BibRef 9909
Earlier: ICCV98(863-869).
IEEE DOI BibRef

Chua, C.S.[Chin-Seng], Ho, Y.K.[Yeong Khing], Liang, Y.,
Rejection of mismatched correspondences along the affine epipolar line,
IVC(18), No. 6-7, 1 May 2000, pp. 445-462.
Elsevier DOI 0003
BibRef

Tang, C.K.[Chi-Keung], and Medioni, G.[Gérard], Lee, M.S.[Mi-Suen],
N-Dimensional Tensor Voting and Application to Epipolar Geometry Estimation,
PAMI(23), No. 8, August 2001, pp. 829-844.
IEEE DOI BibRef 0108 USC Computer Vision 0109
BibRef
Earlier:
Epipolar Geometry Estimation by Tensor Voting in 8D,
ICCV99(502-509).
IEEE DOI The tensor voting formulation (
See also Computational Framework for Segmentation and Grouping, A. ) for Stereo applications. BibRef

Tong, W.S.[Wai-Shun], Tang, C.K.[Chi-Keung], Medioni, G.[Gerard],
Simultaneous Two-View Epipolar Geometry Estimation and Motion Segmentation by 4D Tensor Voting,
PAMI(26), No. 9, September 2004, pp. 1167-1184.
IEEE Abstract. 0409
BibRef
Earlier:
Epipolar Geometry Estimation for Non-Static Scenes by 4D Tensor Voting,
CVPR01(I:926-933).
IEEE DOI BibRef USC Computer Vision 0110
BibRef

Wu, T.P.[Tai-Pang], Yeung, S.K.[Sai-Kit], Jia, J.Y.[Jia-Ya], Tang, C.K.[Chi-Keung],
Quasi-dense 3D reconstruction using tensor-based multiview stereo,
CVPR10(1482-1489).
IEEE DOI 1006
BibRef

Mellor, J.P.,
Geometry and Texture from Thousands of Images,
IJCV(51), No. 1, January 2003, pp. 5-35.
DOI Link 0211
BibRef
Earlier: SMILE00(170 ff.).
Springer DOI 0209
BibRef

Mellor, J.P., Teller, S.[Seth], Lozano-Perez, T.[Thomas],
Dense Surface Patches from Thousands of Pose Iamges,
DARPA98(537-542). BibRef 9800
Earlier:
Dense Depth Maps from Epipolar Images,
DARPA97(893-900). BibRef
And: MIT AI Memo-1593, November 1996.
WWW Link. BibRef

Mellor, J.P.[John P.],
Automatically Recovering Geometry and Texture from Large Sets of Calibrated Images,
Ph.D.Thesis, Massachusetts Institute of Technology, 1999.
PDF File. BibRef 9900
And: MIT AI TR1674, October 1999.
WWW Link. BibRef

Berestov, A.L.[Alexander L.],
Fast epipolar line adjustment of stereo pairs,
US_Patent6,671,399, Dec 30, 2003
WWW Link. BibRef 0312

Nistér, D.[David], Schaffalitzky, F.[Frederik],
Four Points in Two or Three Calibrated Views: Theory and Practice,
IJCV(67), No. 2, April 2006, pp. 211-231.
Springer DOI 0605
BibRef
Earlier:
What Do Four Points in Two Calibrated Images Tell Us about the Epipoles?,
ECCV04(Vol II: 41-57).
Springer DOI 0405

See also How Hard is 3-View Triangulation Really?. BibRef

Kahl, F.[Fredrik], Henrion, D.[Didier],
Globally Optimal Estimates for Geometric Reconstruction Problems,
IJCV(74), No. 1, August 2007, pp. 3-15.
Springer DOI 0705
BibRef
Earlier: ICCV05(II: 978-985).
IEEE DOI 0510
Award, Marr Prize. Apply to a number of vision problems (reconstruction, epipolar estimation). BibRef

Hu, M.X.[Ming-Xing], McMenemy, K.[Karen], Ferguson, S.[Stuart], Dodds, G.[Gordon], Yuan, B.Z.[Bao-Zong],
Epipolar geometry estimation based on evolutionary agents,
PR(41), No. 2, February 2008, pp. 575-591.
Elsevier DOI 0711
BibRef
Earlier:
Robust Projective Reconstruction with Missing Information,
ICPR06(I: 547-550).
IEEE DOI 0609
Epipolar geometry; Evolutionary agent; Fundamental matrix; Robust estimation; Evolutionary behavior; Subset template BibRef

Hu, M.X.[Ming-Xing], Yuan, B.Z.[Bao-Zong], Dodds, G., Tang, X.F.[Xiao-Fang],
Robust method of recovering epipolar geometry using messy genetic algorithm,
CRV04(164-171).
IEEE DOI 0408
BibRef

Hu, M.X.[Ming-Xing], Dodds, G., Yuan, B.Z.[Bao-Zong],
Evolutionary agents for epipolar geometry estimation,
ICIP04(III: 1843-1846).
IEEE DOI 0505
BibRef

Hu, M.X.[Ming-Xing], Yuan, B.Z.[Bao-Zong],
Robust estimation of trifocal tensor using messy genetic algorithm,
ICPR02(IV: 347-350).
IEEE DOI 0211
BibRef

Goshen, L.[Liran], Shimshoni, I.[Ilan],
Balanced Exploration and Exploitation Model Search for Efficient Epipolar Geometry Estimation,
PAMI(30), No. 7, July 2008, pp. 1230-1242.
IEEE DOI 0806
BibRef
Earlier: ECCV06(II: 151-164).
Springer DOI 0608
BibRef

Goshen, L.[Liran], Shimshoni, I.[Ilan],
Guided Sampling via Weak Motion Models and Outlier Sample Generation for Epipolar Geometry Estimation,
IJCV(80), No. 2, November 2008, pp. xx-yy.
Springer DOI 0809
BibRef
Earlier: CVPR05(I: 1105-1112).
IEEE DOI 0507
BibRef

Monaco, J.P.[James P.], Bovik, A.C.[Alan C.], Cormack, L.K.[Lawrence K.],
Nonlinearities in Stereoscopic Phase-Differencing,
IP(17), No. 9, September 2008, pp. 1672-1684.
IEEE DOI 0810
BibRef
Earlier:
Stereoscopic Phase-Differencing: Multiscale Synthesis,
Southwest08(33-36).
IEEE DOI 0803
BibRef

Monaco, J.P.[James P.], Bovik, A.C.[Alan C.], Cormack, L.K.[Lawrence K.],
Active, Foveated, Uncalibrated Stereovision,
IJCV(85), No. 2, November 2009, pp. xx-yy.
Springer DOI 0909
BibRef
Earlier:
Epipolar Spaces and Optimal Sampling Strategies,
ICIP07(VI: 545-548).
IEEE DOI 0709
BibRef
And:
Epipolar Spaces for Active Binocular Vision Systems,
ICIP07(VI: 549-551).
IEEE DOI 0709
BibRef

Piao, Y.[Ying], Sato, J.[Jun],
Computing Epipolar Geometry from Unsynchronized Cameras,
IEICE(E91-D), No. 8, August 2008, pp. 2171-2178.
DOI Link 0804
BibRef
Earlier: CIAP07(475-480).
IEEE DOI 0709
BibRef

Wu, H.H.P.[Hsien-Huang P.], Lee, M.T.[Meng-Tu], Weng, P.K.[Ping-Kuo], Chen, S.L.[Soon-Lin],
Epipolar geometry of catadioptric stereo systems with planar mirrors,
IVC(27), No. 8, 2 July 2009, pp. 1047-1061.
Elsevier DOI 0906
Catadioptric Camera. Catadioptric stereo system; Affine epipolar geometry; Fundamental matrix; Reflection transformation BibRef

Heo, Y.S.[Yong Seok], Lee, K.M.[Kyong Mu], Lee, S.U.[Sang Uk],
Robust Stereo Matching Using Adaptive Normalized Cross-Correlation,
PAMI(33), No. 4, April 2011, pp. 807-822.
IEEE DOI 1103
Color values are not always similar in the pair. BibRef

Kim, T.H.[Tae Hoon], Lee, K.M.[Kyoung Mu], Lee, S.U.[Sang Uk],
A Probabilistic Model for Correspondence Problems Using Random Walks with Restart,
ACCV09(III: 416-425).
Springer DOI 0909
BibRef

Jung, H.Y.[Ho Yub], Lee, K.M.[Kyoung Mu], Lee, S.U.[Sang Uk],
Stereo Matching Using Scanline Disparity Discontinuity Optimization,
ACIVS06(588-597).
Springer DOI 0609
BibRef

Yang, Q., Ahuja, N.,
Stereo Matching Using Epipolar Distance Transform,
IP(21), No. 10, October 2012, pp. 4410-4419.
IEEE DOI 1209
BibRef

Brahmachari, A.S.[Aveek Shankar], Sarkar, S.[Sudeep],
Hop-Diffusion Monte Carlo for Epipolar Geometry Estimation between Very Wide-Baseline Images,
PAMI(35), No. 3, March 2013, pp. 755-762.
IEEE DOI 1303
BibRef
Earlier:
BLOGS: Balanced local and global search for non-degenerate two view epipolar geometry,
ICCV09(1685-1692).
IEEE DOI 0909
Balanced LOcal and Global Search. Estimate epipolar geometry between 2 cameras, without a priori correspondences. BibRef

Zhang, D.[Dazhi], Wang, Y.T.[Yong-Tao], Tao, W.B.[Wen-Bing], Xiong, C.Y.[Cheng-Yi],
Epipolar geometry estimation for wide baseline stereo by Clustering Pairing Consensus,
PRL(36), No. 1, 2014, pp. 1-9.
Elsevier DOI 1312
Wide baseline match BibRef

Bentolila, J.[Jacob], Francos, J.M.[Joseph M.],
Conic epipolar constraints from affine correspondences,
CVIU(122), No. 1, 2014, pp. 105-114.
Elsevier DOI 1404
Epipolar geometry BibRef

Kushnir, M.[Maria], Shimshoni, I.[Ilan],
Epipolar Geometry Estimation for Urban Scenes with Repetitive Structures,
PAMI(36), No. 12, December 2014, pp. 2381-2395.
IEEE DOI 1411
BibRef
Earlier: ACCV12(IV:163-176).
Springer DOI 1304
Algorithm design and analysis BibRef

Lai, T.T.[Tao-Tao], Wang, H.Z.[Han-Zi], Yan, Y.[Yan], Xiao, G.B.[Guo-Bao], Suter, D.[David],
Efficient guided hypothesis generation for multi-structure epipolar geometry estimation,
CVIU(154), No. 1, 2017, pp. 152-165.
Elsevier DOI 1612
Epipolar geometry estimation BibRef

Agarwal, S.[Sameer], Lee, H.L.[Hon-Leung], Sturmfels, B.[Bernd], Thomas, R.R.[Rekha R.],
On the Existence of Epipolar Matrices,
IJCV(121), No. 3, February 2017, pp. 403-415.
Springer DOI 1702
BibRef

Tron, R.[Roberto], Daniilidis, K.[Kostas],
The Space of Essential Matrices as a Riemannian Quotient Manifold,
SIIMS(10), No. 3, 2017, pp. 1416-1445.
DOI Link 1710
BibRef
Earlier:
On the Quotient Representation for the Essential Manifold,
CVPR14(1574-1581)
IEEE DOI 1409
Riemannian geometry; epipolar constraint; essential manifold BibRef

Goldman, Y.[Yehonatan], Rivlin, E.[Ehud], Shimshoni, I.[Ilan],
Robust epipolar geometry estimation using noisy pose priors,
IVC(67), No. 1, 2017, pp. 16-28.
Elsevier DOI 1710
Robust estimation BibRef

Neri, A., Carli, M., Battisti, F.,
A Maximum Likelihood Approach for Depth Field Estimation Based on Epipolar Plane Images,
IP(28), No. 2, February 2019, pp. 827-840.
IEEE DOI 1811
computational complexity, image resolution, maximum likelihood estimation, optimisation, microlens array, maximum likelihood BibRef

Darmon, F.[François], Monasse, P.[Pascal],
The Polar Epipolar Rectification,
IPOL(11), 2021, pp. 56-75.
DOI Link 2103
Code, Stereo.
See also Epipolar geometry and log-polar transform in wide baseline stereo matching. BibRef

Wang, X.[Xuanqi], Wang, F.[Feng], Xiang, Y.M.[Yu-Ming], You, H.J.[Hong-Jian],
A General Framework of Remote Sensing Epipolar Image Generation,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Chang, J.H.[Jia-Hao], He, J.F.[Jian-Feng], Zhang, T.Z.[Tian-Zhu], Yu, J.[Jiyang], Wu, F.[Feng],
EI-MVSNet: Epipolar-Guided Multi-View Stereo Network With Interval-Aware Label,
IP(33), 2024, pp. 753-766.
IEEE DOI 2402
Costs, Estimation, Feature extraction, Three-dimensional displays, Learning systems, Image reconstruction, Aggregates, interval-aware BibRef

Chang, J.H.[Jia-Hao], Yu, J.H.[Jia-Huan], Zhang, T.Z.[Tian-Zhu],
Structured Epipolar Matcher for Local Feature Matching,
IMW23(6177-6186)
IEEE DOI 2309
BibRef

Zhong, L.[Lin], Zong, B.C.[Bang-Cheng], Wang, Q.M.[Qi-Ming], Yu, J.[Junle], Zhou, W.H.[Wen-Hui],
Implicit Epipolar Geometric Function based Light Field Continuous Angular Representation,
LightField23(3463-3472)
IEEE DOI 2309
BibRef

Bangunharcana, A.[Antyanta], Magd, A.[Ahmed], Kim, K.S.[Kyung-Soo],
DualRefine: Self-Supervised Depth and Pose Estimation Through Iterative Epipolar Sampling land Refinement Toward Equilibrium,
CVPR23(726-738)
IEEE DOI 2309

WWW Link. BibRef

Huang, B.[Baoru], Zheng, J.Q.[Jian-Qing], Giannarou, S.[Stamatia], Elson, D.S.[Daniel S.],
H-Net: Unsupervised Attention-based Stereo Depth Estimation Leveraging Epipolar Geometry,
WAD22(4459-4466)
IEEE DOI 2210
Geometry, Training, Supervised learning, Semantics, Estimation, Computer architecture BibRef

Larsson, V.[Viktor], Pollefeys, M.[Marc], Oskarsson, M.[Magnus],
Orthographic-Perspective Epipolar Geometry,
ICCV21(5550-5558)
IEEE DOI 2203
Geometry, Photography, Satellites, Spaceborne radar, Cameras, Calibration, Radar applications, Stereo, BibRef

Zhou, Q.[Qunjie], Sattler, T.[Torsten], Leal-Taixé, L.[Laura],
Patch2Pix: Epipolar-Guided Pixel-Level Correspondences,
CVPR21(4667-4676)
IEEE DOI 2111
Location awareness, Geometry, Visualization, Semantics, Pipelines, Predictive models, Pattern recognition BibRef

Long, X.X.[Xiao-Xiao], Liu, L.J.[Ling-Jie], Li, W.[Wei], Theobalt, C.[Christian], Wang, W.P.[Wen-Ping],
Multi-view Depth Estimation using Epipolar Spatio-Temporal Networks,
CVPR21(8254-8263)
IEEE DOI 2111
Solid modeling, Limiting, Navigation, Computational modeling, Estimation, Transformers BibRef

Pourian, N., Nestares, O.,
Guided Sparse Feature Matching Via Coarsely Defined Dense Matches,
ICIP20(2770-2774)
IEEE DOI 2011
Visualization, Calibration, Computational efficiency, Feature extraction, Optical imaging, Adaptive optics, Cameras, Epipolar Constraint BibRef

Gaudillière, V., Simon, G., Berger, M.,
Region-Based Epipolar and Planar Geometry Estimation in Low-Textured Environments,
ICIP18(898-902)
IEEE DOI 1809
Estimation, Image segmentation, Geometry, Visualization, Feature extraction, Merging, Robustness, low-textured industrial environments BibRef

Umam, A., Hsieh, Y., Malem Marsya, J., Chuang, J.,
Automatic Generation of Epipolar Curves,
ICIP18(3668-3672)
IEEE DOI 1809
Cameras, Estimation, Geometry, Robot vision systems, Distortion, Task analysis, Epipolar curves, stereo matching BibRef

Kasten, Y., Werman, M.,
Two View Constraints on the Epipoles from Few Correspondences,
ICIP18(888-892)
IEEE DOI 1809
Cameras, Geometry, Mathematical model, Manifolds, Image color analysis, Task analysis, Face, Epipolar Geometry, Multiple View Geometry BibRef

Halperin, T., Werman, M.,
An Epipolar Line from a Single Pixel,
WACV18(983-991)
IEEE DOI 1806
cameras, feature extraction, image motion analysis, stereo image processing, video signal processing, Transmission line matrix methods BibRef

Gong, K., Fritsch, D.,
Relative Orientation And Modified Piecewise Epipolar Resampling For High Resolution Satellite Images,
Hannover17(579-586).
DOI Link 1805
BibRef

Eichhardt, I.[Ivan], Barath, D.[Daniel],
Relative Pose from Deep Learned Depth and a Single Affine Correspondence,
ECCV20(XII: 627-644).
Springer DOI 2010
BibRef

Barath, D.[Daniel], Matas, J.G.[Jiri G.], Hajder, L.[Levente],
Accurate Closed-form Estimation of Local Affine Transformations Consistent with the Epipolar Geometry,
BMVC16(xx-yy).
HTML Version. 1805
BibRef

Garrigues, M., Manzanera, A.,
Fast Semi Dense Epipolar Flow Estimation,
WACV17(427-435)
IEEE DOI 1609
Adaptive optics, Benchmark testing, Cameras, Estimation, Optical computing, Optical imaging BibRef

Bradler, H., Ochs, M., Fanani, N., Mester, R.,
Joint Epipolar Tracking (JET): Simultaneous Optimization of Epipolar Geometry and Feature Correspondences,
WACV17(445-453)
IEEE DOI 1609
Cameras, Geometry, Mathematical model, Optical imaging, Optimization, Symmetric matrices, Tracking BibRef

Matsuzaki, K.[Kohei], Uchida, Y.[Yusuke], Sakazawa, S.[Shigeyuki], Sato, S.[Shin'ichi],
Geometric verification using semi-2D constraints for 3D object retrieval,
ICPR16(2338-2343)
IEEE DOI 1705
Computational modeling, Estimation, Geometry, Image recognition, Image retrieval, Three-dimensional, displays BibRef

Ben-Artzi, G., Halperin, T., Werman, M., Peleg, S.,
Epipolar geometry based on line similarity,
ICPR16(1864-1869)
IEEE DOI 1705
Cameras, Dynamic programming, Geometry, Motion measurement, Robustness, Two, dimensional, displays BibRef

Larsson, V.[Viktor], Fredriksson, J.[Johan], Toft, C.[Carl], Kahl, F.[Fredrik],
Outlier Rejection for Absolute Pose Estimation with Known Orientation,
BMVC16(xx-yy).
HTML Version. 1805
BibRef

Fredriksson, J.[Johan], Larsson, V.[Viktor], Olsson, C.[Carl], Kahl, F.[Fredrik],
Optimal Relative Pose with Unknown Correspondences,
CVPR16(1728-1736)
IEEE DOI 1612
Compute epipolar geometry and correspondences based on geometry. BibRef

Kukelova, Z., Heller, J., Bujnak, M., Fitzgibbon, A., Pajdla, T.,
Efficient Solution to the Epipolar Geometry for Radially Distorted Cameras,
ICCV15(2309-2317)
IEEE DOI 1602
Cameras BibRef

Shah, R.[Rajvi], Srivastava, V.[Vanshika], Narayanan, P.J.,
Geometry-Aware Feature Matching for Structure from Motion Applications,
WACV15(278-285)
IEEE DOI 1503
Approximation algorithms. First a subset to estimate epi-polar geometry, then match the rest. BibRef

Pritts, J., Chum, O., Matas, J.G.,
Approximate models for fast and accurate epipolar geometry estimation,
IVCNZ13(106-111)
IEEE DOI 1402
approximation theory BibRef

Tan, X.[Xiao], Sun, C.M.[Chang-Ming], Sirault, X., Furbank, R., Pham, T.D.,
Feature Correspondence with Even Distribution,
DICTA12(1-7).
IEEE DOI 1303
Stereo matching. BibRef

Lourenco, M., Goncalves, N.,
Fusing appearance and geometric constraints for estimating the epipolar geometry,
WACV13(399-406).
IEEE DOI 1303
BibRef

Rodriguez, A.L., Lopez-de-Teruel, P.E., Ruiz, A.,
GEA optimization for live structureless motion estimation,
Dense11(715-718).
IEEE DOI 1201
Global Epipolar Adjustment. BibRef

Xu, L.F.[Ling-Feng], Au, O.C.[Oscar C.], Sun, W.X.[Wen-Xiu], Li, Y.J.[Yu-Jun], Chui, S.H.[Sung Him], Kwok, C.W.[Chun Wing],
Image rectification for single camera stereo system,
ICIP11(977-980).
IEEE DOI 1201
Use mirrors. Computations to deal with mirrors. BibRef

Herraez, J., Denia, J.L., Navarro, P., Rodriguez, J., Martin, M.T.,
Stereoscopic vision through epipolarization without orientation parameters,
ICIP11(981-984).
IEEE DOI 1201
BibRef

Yang, G.L.[Guo-Lei], Liang, L.H.[Lu-Hong], Gao, W.[Wen],
Fast intra mode selection for stereo video coding using epipolar constraint,
VCIP11(1-4).
IEEE DOI 1201
BibRef

Zilly, F.[Frederik], Mueller, M.[Marcus], Eisert, P.[Peter], Kauff, P.[Peter],
Joint Estimation of Epipolar Geometry and Rectification Parameters using Point Correspondences for Stereoscopic TV Sequences,
3DPVT10(xx-yy).
WWW Link. 1005
BibRef

Triggs, B.[Bill], Bendale, P.[Pashmina],
Epipolar Constraints for Multiscale Matching,
BMVC10(xx-yy).
HTML Version. 1009
BibRef

Bendale, P.[Pashmina], Triggs, B.[Bill], Kingsbury, N.[Nick],
Multiscale Keypoint Analysis based on Complex Wavelets,
BMVC10(xx-yy).
HTML Version. 1009
BibRef

Xu, W.[Wei], Mulligan, J.[Jane],
Feature Matching under Region-Based Constraints for Robust Epipolar Geometry Estimation,
ISVC09(II: 264-273).
Springer DOI 0911
BibRef

Hart, J.[Justin], Scassellati, B.[Brian], Zucker, S.W.[Steven W.],
Epipolar Geometry for Humanoid Robotic Heads,
CogVis08(24-36).
Springer DOI 0805
BibRef

Natsumi, H.[Hiroaki], Sugimoto, A.[Akihiro], Kenmochi, Y.[Yukiko],
Predicting Corresponding Region in a Third View Using Discrete Epipolar Lines,
DGCI08(xx-yy).
Springer DOI 0804
BibRef

Li, W.F.[Wen-Feng], Li, B.X.[Bao-Xin],
MAP Estimation of Epipolar Geometry by EM Algorithm and Local Diffusion,
ICIP07(V: 201-204).
IEEE DOI 0709
BibRef

Engels, C., Nister, D.,
Global Uncertainty in Epipolar Geometry via Fully and Partially Data-Driven Sampling,
BenCOS05(xx-yy).
PDF File. 0510
BibRef

Migita, T.[Tsuyoshi], Shakunaga, T.[Takeshi],
Evaluation of Epipole Estimation Methods with/without Rank-2 Constraint across Algebraic/Geometric Error Functions,
CVPR07(1-7).
IEEE DOI 0706
BibRef

Barreto, J.P.[Joao P.], Daniilidis, K.[Kostas],
Epipolar Geometry of Central Projection Systems Using Veronese Maps,
CVPR06(I: 1258-1265).
IEEE DOI 0606
BibRef

Chum, O., Werner, T., Pajdla, T.,
Joint Orientation of Epipoles,
BMVC03(xx-yy).
HTML Version. 0409
BibRef

Perdoch, M.[Michal], Matas, J.G.[Jiri G.], Chum, O.[Ondrej],
Epipolar Geometry from Two Correspondences,
ICPR06(IV: 215-219).
IEEE DOI 0609
BibRef

Chum, O.[Ondrej], Werner, T.[Tomas], Matas, J.G.[Jiri G.],
Two-View Geometry Estimation Unaffected by a Dominant Plane,
CVPR05(I: 772-779).
IEEE DOI 0507
BibRef
Earlier:
Epipolar geometry estimation via RANSAC benefits from the oriented epipolar constraint,
ICPR04(I: 112-115).
IEEE DOI 0409
BibRef

Werner, T.[Tomas], Pajdla, T.[Tomas],
Cheirality in Epipolar Geometry,
ICCV01(I: 548-553).
IEEE DOI 0106
Not all points on the epipolar line correspond to possible configurations. BibRef

Pollefeys, M.[Marc], Sinha, S.N.[Sudipta N.],
Iso-disparity Surfaces for General Stereo Configurations,
ECCV04(Vol III: 509-520).
Springer DOI 0405
Same resolution along the epipolar line in both images. BibRef

Feldmann, I., Kauff, P., Eisert, P.,
Optimized space sampling for circular image cube trajectory analysis,
ICIP04(III: 1947-1950).
IEEE DOI 0505
BibRef
And: A1, A3, A2:
Extension of epipolar image analysis to circular camera movements,
ICIP03(III: 697-700).
IEEE DOI 0312
BibRef

Matousek, M.[Martin], Hlavác, V.[Václav],
Epipolar Plane Images as a Tool to Seek Correspondences in a Dense Sequence,
CAIP03(74-81).
Springer DOI 0311
BibRef

Jahn, H.[Herbert],
Parallel Approach to Binocular Stereo Matching,
PCV02(A: 175). 0305
BibRef

Jahn, H.[Herbert],
Binocular Stereo Matching by Local Attraction,
CAIP01(676 ff.).
Springer DOI 0210
BibRef

Jahn, H.[Herbert],
Parallel Epipolar Stereo Matching,
ICPR00(Vol I: 402-405).
IEEE DOI 0009
BibRef

Kurata, T.[Takeshi], Sakaue, K.[Katsuhiko], Fujiki, J.[Jun],
Affine Epipolar Geometry via Factorization Method,
ICPR98(Vol I: 862-866).
IEEE DOI 9808
BibRef

Ishikawa, H., Geiger, D.,
Occlusions, discontinuities, and epipolar lines in stereo,
ECCV98(I: 232).
Springer DOI BibRef 9800

Kahl, F.[Fredrik], and Heyden, A.[Anders],
Using Conic Correspondence in Two Images to Estimate the Epipolar Geometry,
ICCV98(761-766).
IEEE DOI BibRef 9800

Ke, Q.[Qifa], Xu, G.[Gang], and Ma, S.D.[Song De],
Recovering Epipolar Geometry by Reactive Tabu Search,
ICCV98(767-771).
IEEE DOI BibRef 9800

Garcia, B.[Blanca], and Brunet, P.[Pere],
3D Reconstruction with Projective Octrees and Epipolar Geometry,
ICCV98(1067-1072).
IEEE DOI BibRef 9800

Chou, G.T.[George T.], Teller, S.[Seth],
Multi-Level 3D Reconstruction with Visibility Constraints,
DARPA98(543-550). BibRef 9800

Chou, G.T.[George T.],
Large-Scale 3D Reconstruction: A Triangulation-Based Approach,
Ph.D.Thesis, Massachusetts Institute of Technology, 2000.
PDF File. BibRef 0001

Chapter on Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular continues in
Stereo Analysis - Boundaries of Curved Surfaces .