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,
Pattern recognition, 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 .