10.1.3 Edge Based Stereo Analysis: Scan Line Oriented

Chapter Contents (Back)
Stereo, Epipolar. Edges. Matching, Edges. Stereo, Edges. Stereo, Scan Line. This section includes the stereo work of Baker and others.

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
BibRef

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
BibRef

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 BibRef

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 BibRef

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 BibRef


Kuang, Z.F.[Zheng-Fei], Li, J.[Jiaman], He, M.M.[Ming-Ming], Wang, T.[Tong], Zhao, Y.J.[Ya-Jie],
DenseGAP: Graph-Structured Dense Correspondence Learning with Anchor Points,
ICPR22(542-549)
IEEE DOI 2212
Costs, Correlation, Image edge detection, Neural networks, Estimation BibRef

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 BibRef

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 BibRef

Peņa, D.[Dexmont], Sutherland, A.[Alistair],
Disparity Estimation by Simultaneous Edge Drawing,
3DModelApp16(II: 124-135).
Springer DOI 1704
BibRef
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 .


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