Levine, M.D.[Martin D.],
O'Handley, D.A.[Douglas A.],
Yagi, G.M.[Gary M.],
Computer Determination of Depth Maps,
CGIP(2), No. 2, October 1973, pp. 131-150.
Elsevier DOI
Stereo, Epipolar. Looks along the scan line and uses the order to constrain the match.
If the constraints are there, stereo is easy.
This idea is used even more heavily by the later work.
BibRef
7310
O'Handley, D.A.,
Scene Analysis in Support of a Mars Rover,
CGIP(2), 1973, pp. 281-297.
BibRef
7300
Helava, U.V.[Unno V.],
Whiteside, A.E.[Arliss E.],
Brummn, G.A.[Gerald A.],
Parallel Line Scanning System for Stereomapping,
US_Patent3,901,595, Aug 1975
WWW Link.
BibRef
7508
Henderson, R.L.,
Miller, W.J., and
Grosch, C.B.,
Automatic Stereo Reconstruction of Man-Made Targets,
SPIE(186), Digital Processing of Aerial Images,
Huntsville, AL, May 1979, pp. 240-248.
Edge matching along epipolar lines. Matches both edges and
the points in between.
BibRef
7905
Baker, H.H.[Harlyn H.],
Edge-Based Stereo Correlation,
DARPA80(168-175). Early version of his work.
BibRef
8000
Baker, H.H., and
Binford, T.O.,
A System for Automated Stereo Mapping,
DARPA82(215-222).
This work uses edges in stereo views and uses the camera model
information to restrict the search to one scan line in the second
view. The final match is also constrained by the order of matching
edges along the scan line. The matching is performed at various
resolutions with the approximate low resolution results used by the
higher resolution matcher. Connectivity of edge points is used to
match points from one scan line to the next. Areas between matching
edges are filled in with intensity based correlation using
constraints from the edge based matching to limit the search.
BibRef
8200
Baker, H.H.[Harlyn H.],
Binford, T.O.[Thomas O.],
Malik, J.[Jitendra], and
Meller, J.F.[Jean-Frederic],
Progress in Stereo Mapping,
DARPA83(327-335).
Recent results of the edge based stereo system.
BibRef
8300
Baker, H.H., and
Binford, T.O.,
Depth from Edge and Intensity Based Stereo,
IJCAI81(631-636).
BibRef
8100
And: A1 only:
Ph.D.Thesis (CS Illinois), 1982.
BibRef
Stanford AIMemo 347, September 1982,
or Stanford CS Memo
BibRef
STAN-CS-82-930.
Matching, Edges. Initial matching based on the edges and stereo camera constraints
(order of edges and line in second image), with extensions to get
the areas between the edges based on intensity information.
Tested on synthetic images and terrain data.
BibRef
McKeown, D.M., and
Hsieh, Y.C.,
Hierarchical Waveform Matching:
A New Feature-Based Stereo Technique,
CVPR92(513-519).
IEEE DOI Scanline match with multiple resolutions.
BibRef
9200
Raju, G.V.S., and
Binford, T.O., and
Shekher, S.,
Stereo Matching Using Viterbi Algorithm,
DARPA87(766-776). Match
the surfaces between edges.
BibRef
8700
Takamura, J., and
Binford, T.O.,
Stereo Modeling System: A Geometric Modeling System
for Modeling Object Instance and Class,
DARPA84(302-307).
BibRef
8400
Lehner, M., and
Gill, R., 1992:
Semi-automatic derivation of digital
elevation models from stereoscopic 3-line scanner data,
ISPRS(29, B4), 1992, pp. 68-75.
BibRef
9200
Adjouadi, M.,
Candocia, F.,
A Stereo Matching Paradigm-Based on the Walsh Transformation,
PAMI(16), No. 12, December 1994, pp. 1212-1218.
IEEE DOI Uses Walsh transform values rather than edges.
BibRef
9412
Candocia, F.,
Adjouadi, M.,
A Similarity Measure for Stereo Feature Matching,
IP(6), No. 10, October 1997, pp. 1460-1464.
IEEE DOI
9710
BibRef
Hongo, S.,
Sonehara, N.,
Yoroizawa, I.,
Edge-Based Binocular Stereopsis Algorithm:
A Matching Mechanism with Probabilistic Feedback,
NeurNet(9), No. 3, April 1996, pp. 379-395.
9605
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Chuang, J.H.,
Chiu, J.M.,
Chen, Z.,
Obtaining Base Edge Correspondence in Stereo Images via
Quantitative Measures Along C-Diagonals,
PRL(18), No. 1, January 1997, pp. 87-95.
9704
BibRef
Goulermas, J.Y.,
Liatsis, P.,
Hybrid symbiotic genetic optimisation for robust edge-based stereo
correspondence.,
PR(34), No. 12, December 2001, pp. 2477-2496.
Elsevier DOI
0110
BibRef
Goulermas, J.Y.,
Liatsis, P.,
A new parallel feature-based stereo-matching algorithm with figural
continuity preservation, based on hybrid symbiotic genetic algorithms,
PR(33), No. 3, March 2000, pp. 529-531.
Elsevier DOI
0001
BibRef
Goulermas, J.Y.,
Liatsis, P.,
Fernando, T.,
A Constrained Nonlinear Energy Minimization Framework for the
Regularization of the Stereo Correspondence Problem,
CirSysVideo(15), No. 4, April 2005, pp. 550-565.
IEEE Abstract.
0501
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Moallem, P.[Payman],
Faez, K.[Karim],
Haddadnia, J.[Javad],
Fast Edge-Based Stereo Matching Algorithm through
Search Space Reduction,
IEICE(E85-D), No. 11, November 2002, pp. xx-yy.
BibRef
0211
Moallem, P.[Payman],
Faez, K.[Karim],
Haddadnia, J.,
Reduction of the Search Space Region in the Edge Based Stereo
Correspondence,
ICIP01(II: 149-152).
IEEE DOI
0108
BibRef
Moallem, P.,
Faez, K.,
Fast Edge-Based Stereo Matching Algorithm based
on Search Space Reduction,
NNSP02(587-596).
WWW Link.
BibRef
0200
Moallem, P.,
Faez, K.,
Search space reduction in the edge based stereo matching by context
of disparity gradient limit,
IWISPA01(164-169), Pula, Croacia, June 19-21, 2001.
BibRef
0106
Moallem, P.,
Faez, K.,
Search Space Reduction in the Edge Based Stereo Correspondence,
VMV01(xx-yy).
PDF File.
0209
BibRef
Oisel, L.,
Memin, E.,
Morin, L.,
Galpin, F.,
One-dimensional dense disparity estimation for three-dimensional
reconstruction,
IP(12), No. 9, September 2003, pp. 1107-1119.
IEEE DOI
0308
BibRef
Oisel, L.,
Morin, L.,
Memin, E.,
Labit, C.,
Planar facets segmentation using a multiresolution dense disparity
field estimation,
ICIP98(II: 617-621).
IEEE DOI
9810
BibRef
Moallem, P.,
Faez, K.,
Effective Parameters in Search Space Reduction Used in a
Fast Edge-Based Stereo Matching,
JCSC(14), No. 2, 2005, pp. 249-266.
HTML Version.
BibRef
0500
Sun, X.[Xun],
Mei, X.[Xing],
Jiao, S.H.[Shao-Hui],
Zhou, M.C.[Ming-Cai],
Liu, Z.H.[Zhi-Hua],
Wang, H.T.[Hai-Tao],
Real-time local stereo via edge-aware disparity propagation,
PRL(49), No. 1, 2014, pp. 201-206.
Elsevier DOI
1410
Stereo matching
BibRef
Kordelas, G.A.[Georgios A.],
Alexiadis, D.S.[Dimitrios S.],
Daras, P.[Petros],
Izquierdo, E.[Ebroul],
Enhanced disparity estimation in stereo images,
IVC(35), No. 1, 2015, pp. 31-49.
Elsevier DOI
1503
BibRef
Earlier:
Revisiting guided image filter based stereo matching and scanline
optimization for improved disparity estimation,
ICIP14(3803-3807)
IEEE DOI
1502
Stereo vision.
Benchmark testing
BibRef
Kordelas, G.A.[Georgios A.],
Alexiadis, D.S.[Dimitrios S.],
Daras, P.[Petros],
Izquierdo, E.[Ebroul],
Content-Based Guided Image Filtering, Weighted Semi-Global
Optimization, and Efficient Disparity Refinement for Fast and
Accurate Disparity Estimation,
MultMed(18), No. 2, February 2016, pp. 155-170.
IEEE DOI
1601
Estimation
BibRef
Kordelas, G.A.[Georgios A.],
Daras, P.[Petros],
Klavdianos, P.,
Izquierdo, E.[Ebroul],
Zhang, Q.,
Accurate stereo 3D point cloud generation suitable for multi-view
stereo reconstruction,
VCIP14(307-310)
IEEE DOI
1504
image reconstruction
BibRef
Vretos, N.[Nicholas],
Daras, P.[Petros],
Temporal and color consistent disparity estimation in stereo videos,
ICIP14(3798-3802)
IEEE DOI
1502
Computer vision
BibRef
Yan, T.,
Gan, Y.,
Xia, Z.,
Zhao, Q.,
Segment-Based Disparity Refinement With Occlusion Handling for Stereo
Matching,
IP(28), No. 8, August 2019, pp. 3885-3897.
IEEE DOI
1907
image matching, image segmentation, Markov processes, optimisation,
probability, stereo image processing, two-layer optimization,
Bayesian inference
BibRef
Yang, X.W.[Xiao-Wei],
Feng, Z.G.[Zhi-Guo],
Zhao, Y.[Yong],
Zhang, G.Y.[Gui-Ying],
He, L.[Lin],
Edge supervision and multi-scale cost volume for stereo matching,
IVC(117), 2022, pp. 104336.
Elsevier DOI
2112
Stereo matching, Geometric constraints,
Multi-scale cost volume, Disparity refinement network
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Wei, H.[Hui],
Meng, L.[Lingjiang],
An accurate stereo matching method based on color segments and edges,
PR(133), 2023, pp. 108996.
Elsevier DOI
2210
Binocular vision, Stereo matching, Industrial robot
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Fan, S.M.[Shi-Meng],
Sun, W.[Wei],
Zheng, J.[Jin],
Fu, Q.[Qiang],
Xue, M.[Min],
Wu, W.[Wei],
Accurate edge-preserving stereo matching by enhancing anisotropy,
SP:IC(114), 2023, pp. 116945.
Elsevier DOI
2305
Stereo matching, Edge preservation, Anisotropy,
Weighted averaging, Cost aggregation
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Zhang, J.W.[Jia-Wei],
Huang, L.[Lei],
Bai, X.[Xiao],
Zheng, J.[Jin],
Gu, L.[Lin],
Hancock, E.R.[Edwin R.],
Exploring the Usage of Pre-trained Features for Stereo Matching,
IJCV(132), No. 10, October 2024, pp. 4305-4326.
Springer DOI
2410
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Wang, J.L.[Jia-Liang],
Zickler, T.E.[Todd E.],
Level Set Stereo for Cooperative Grouping With Occlusion,
ICIP21(3198-3202)
IEEE DOI
2201
Geometry, Image coding, Level set, Stereo, level set, occlusion,
cooperative optimization, variational method
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Wang, J.L.[Jia-Liang],
Zickler, T.E.[Todd E.],
Local Detection of Stereo Occlusion Boundaries,
CVPR19(3813-3822).
IEEE DOI
2002
BibRef
Wang, J.L.,
Glasner, D.,
Zickler, T.E.,
Toward Perceptually-Consistent Stereo: A Scanline Study,
ICCV17(1557-1565)
IEEE DOI
1802
image matching, stereo image processing, visual perception,
computational stereo systems, correlation cues, decorrelation,
Visualization
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Peņa, D.[Dexmont],
Sutherland, A.[Alistair],
Disparity Estimation by Simultaneous Edge Drawing,
3DModelApp16(II: 124-135).
Springer DOI
1704
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And:
Non-parametric image transforms for sparse disparity maps,
MVA15(291-294)
IEEE DOI
1507
Benchmark testing
BibRef
Yu, Z.[Zhan],
Guo, X.Q.[Xin-Qing],
Ling, H.B.[Hai-Bing],
Lumsdaine, A.[Andrew],
Yu, J.Y.[Jing-Yi],
Line Assisted Light Field Triangulation and Stereo Matching,
ICCV13(2792-2799)
IEEE DOI
1403
Light Field Stereo Matching; Light Field Triangulation
BibRef
Witt, J.[Jonas],
Weltin, U.[Uwe],
Sparse stereo by edge-based search using dynamic programming,
ICPR12(3631-3635).
WWW Link.
1302
BibRef
Cheng, F.Y.[Fei-Yang],
Zhang, H.[Hong],
Sun, M.G.[Min-Gui],
Wang, H.L.[He-Long],
Yuan, D.[Ding],
Cross-Trees for Stereo Matching with Priors,
ICPR14(208-213)
IEEE DOI
1412
Accuracy
BibRef
Cheng, F.Y.[Fei-Yang],
Zhang, H.[Hong],
Yuan, D.[Ding],
Sun, M.G.[Min-Gui],
Stereo Matching with Global Edge Constraint and Occlusion Handling,
DICTA12(1-6).
IEEE DOI
1303
BibRef
Zhang, H.[Hong],
Cheng, F.Y.[Fei-Yang],
Yuan, D.[Ding],
Li, Y.C.[Yue-Cheng],
Sun, M.G.[Min-Gui],
Stereo matching with Global Edge Constraint and Graph Cuts,
ICPR12(372-375).
WWW Link.
1302
BibRef
Hu, G.[Gang],
Zhao, Y.[Yong],
Yuan, Y.[Yule],
Gu, D.G.[Dong-Ge],
Local stereo matching with canny segmentation and reliable seed
propagation,
CVRS12(177-182).
IEEE DOI
1302
BibRef
Guan, S.S.[Shu-Shi],
Klette, R.[Reinhard],
Woo, Y.W.[Young W.],
Belief Propagation for Stereo Analysis of Night-Vision Sequences,
PSIVT09(932-943).
Springer DOI
0901
BibRef
Guan, S.S.[Shu-Shi],
Klette, R.[Reinhard],
Belief-Propagation on Edge Images for Stereo Analysis of Image
Sequences,
RobVis08(291-302).
Springer DOI
0802
BibRef
Su, X.Y.[Xiao-Yuan],
Khoshgoftaar, T.M.[Taghi M.],
Arbitrarily-Shaped Window Based Stereo Matching using the Go-Light
Optimization Algorithm,
ICIP07(VI: 556-559).
IEEE DOI
0709
BibRef
Su, X.Y.[Xiao-Yuan],
Khoshgoftaar, T.M.[Taghi M.],
A Progressive Edge-Based Stereo Correspondence Method,
ISVC07(I: 248-257).
Springer DOI
0711
BibRef
Wu, C.C.[Chang-Chang],
Wang, Z.F.[Zeng-Fu],
Stereo Correspondence Using Stripe Adjacency Graph,
ICPR06(I: 123-126).
IEEE DOI
0609
BibRef
Chapter on Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular continues in
EpiPolar Analysis .