10.1.8 Stereo Analysis: Regions, Combine Area and Edge

Nishiya, T.[Takushi],
Position measuring method,
US_Patent4,825,393, Apr 25, 1989
WWW Link. BibRef 8904

Fleck, M.M.,
A Topological Stereo Matcher,
IJCV(6), No. 3, August 1991, pp. 197-226.
Springer DOI Works for large angle and disparity differences, but the local structure must be consistent.
See also Boundaries and Topological Algorithms. BibRef 9108

Fleck, M.M.[Margaret M.],
Perspective Projection: The Wrong Imaging Model,
Univ. IowaCS TR 95-01, 1995.
PS File. BibRef 9500

Cochran, S.D.,
Surface Description from Binocular Stereo,
USC_IRISTR-264, November 1990, BibRef 9011 Ph.D.Thesis (Comp. Eng.). BibRef USC Computer VisionOther papers are preliminary to this one. Stereo analysis with area based and feature based processing. Lots of results. BibRef

Cochran, S.D., and Medioni, G.G.,
3-D Surface Description from Binocular Stereo,
PAMI(14), No. 10, October 1992, pp. 981-994.
IEEE DOI
HTML Version. BibRef 9210 USC Computer Vision BibRef
Earlier:
Accurate Surface Description for Binocular Stereo,
DARPA89(857-869). BibRef
And: 3DWS89(16-23). The paper derived from the thesis work. A large variety of results. Combining edge and area approaches to eliminate errors and improve the results of reconstructions based on stereo. BibRef

Cochran, S.D., Medioni, G.G., and Nevatia, R.,
Correcting Matches and Inferring Surface Patches in Passive Stereo,
CVWS87(333-335). BibRef 8700 USC Computer Vision
HTML Version. BibRef
Earlier: A2, A3 Only:
Steps Toward Accurate Stereo Correspondence,
DARPA87(777-791).
HTML Version. Stereo matching taking lines and regions and getting surfaces. BibRef

Hoff, W.[William], and Ahuja, N.[Narendra],
Surfaces from Stereo: Integrating Feature Matching, Disparity Estimation, and Contour Detection,
PAMI(11), No. 2, February 1989, pp. 121-136.
IEEE DOI BibRef 8902
Earlier:
Extracting Surfaces from Stereo Images: an Integrated Approach,
ICCV87(284-294), BibRef
Surfaces from Stereo,
ICPR86(516-518), BibRef
And: DARPA85(98-106). BibRef
And:
Depth from Stereo,
CVPR85(NOT in the proceedings). Integrate the 3D determined from stereo with the 3D reconstructions and require them to agree. BibRef

Hoff, W.A.,
Surfaces from Stereo: An Integrated Approach,
Ph.D.1987. BibRef 8700 Illinoisat Urbana-Champaign. BibRef

McKeown, D.M., and Perlant, F.P.,
Refinement of Disparity Estimates Through the Fusion of Monocular Image Segmentations,
CVPR92(486-492).
IEEE DOI BibRef 9200
And: DARPA92(839-855). Stereo, Regions. Considerable improvement of the results using fusion. BibRef

Hsieh, Y.C.[Yuan C.], McKeown, Jr., D.M.[David M.], Perlant, F.P.[Frederic P.],
Performance Evaluation of Scene Registration and Stereo Matching for Cartographic Feature Extraction,
PAMI(14), No. 2, February 1992, pp. 214-238.
IEEE DOI BibRef 9202
Earlier: CMU-CS-TR-90-193, CMU CS Dept., November 1990. BibRef
Earlier: A1, A3, A2:
Recovering 3D Information from Complex Aerial Imagery,
DARPA90(670-691). BibRef
And: ICPR90(I: 136-146).
IEEE DOI Application, Cartography. Stereo, Evaluation. Matching, Evaluation. Stereo by merging line based processes and area based. Uses the earlier scene registration work. Comparison with ground truth results. BibRef

Mclauchlan, P.F.[Philip F.], Mayhew, J.E.W.[John E.W.], Frisby, J.P.[John P.],
Stereoscopic Recovery and Description of Smooth Textured Surfaces,
IVC(9), No. 1, February 1991, pp. 20-26.
Elsevier DOI BibRef 9102
Earlier: BMVC90(xx-yy).
PDF File. 9009
BibRef

Fua, P.V.,
A Parallel Stereo Algorithm That Produces Dense Depth Maps and Preserves Image Features,
MVA(6), No. 1, Winter 1993, pp. 35-49. BibRef 9300
And: INRIAresearch report 1369. BibRef

Huynh, D.Q., Owens, R.A.,
Line Labeling And Region-Segmentation In Stereo Image Pairs,
IVC(12), No. 4, May 1994, pp. 213-225.
Elsevier DOI BibRef 9405

Pong, T.C., Haralick, R.M., Shapiro, L.G.,
Matching Topographic Structures in Stereo Vision,
PRL(9), 1989, pp. 127-136. BibRef 8900

Super, B.J., Klarquist, W.N.,
Patch-Based Stereo in a General Binocular Viewing Geometry,
PAMI(19), No. 3, March 1997, pp. 247-253.
IEEE DOI 9704
BibRef
Earlier:
Patch Matching and Stereopsis in a General Stereo Viewing Geometry,
Univ. of TexasTR 94-006, November 1994, Revised February 1995. Gets 3-D planar patches from image patch matches. BibRef

Rojas, A., Calvo, A., Munoz, J.,
A Dense Disparity Map of Stereo Images,
PRL(18), No. 4, April 1997, pp. 385-393. 9708
BibRef

Wei, G.Q.[Guo-Qing], Brauer, W.[Wilfried], Hirzinger, G.[Gerd],
Intensity-Based and Gradient-Based Stereo Matching Using Hierarchical Gaussian Basis Functions,
PAMI(20), No. 11, November 1998, pp. 1143-1160.
IEEE DOI 9811
Minimize intensity and gradient errors together. Dense depth maps from stereo images. BibRef

Valentinotti, F., Taraglio, S.,
A hybrid approach for stereo disparity computation,
MVA(11), No. 4, 1999, pp. 161-170.
Springer DOI 0001
BibRef

Boufama, B.S.[Boubakeur S.],
Using geometry towards stereo dense matching,
PR(33), No. 5, May 2000, pp. 871-873.
Elsevier DOI 0003
BibRef
Earlier:
The Use of Homographies for View Synthesis,
ICPR00(Vol I: 563-566).
IEEE DOI 0009
BibRef

Boufama, B., O'Connell, D.,
Region segmentation and matching in stereo images,
ICPR02(III: 631-634).
IEEE DOI 0211
BibRef

Amintabar, A.[Amirhasan], Boufama, B.[Boubakeur],
The Distinction between Virtual and Physical Planes Using Homography,
ICIAR09(727-736).
Springer DOI 0907
BibRef
Earlier:
Homography-based plane identification and matching,
ICIP08(297-300).
IEEE DOI 0810
BibRef

Han, K.P.[Kyu-Phil], Bae, T.M.[Tae-Min], Ha, Y.H.[Yeong-Ho],
Hybrid stereo matching with a new relaxation scheme of preserving disparity discontinuity,
PR(33), No. 5, May 2000, pp. 767-785.
Elsevier DOI 0003
Combined edge and region. BibRef

López, A.[Angeles], Pla, F.[Filiberto],
Dealing with segmentation errors in region-based stereo matching,
PR(33), No. 8, August 2000, pp. 1325-1338.
Elsevier DOI 0005
Segmentation errors in region-based approaches. BibRef

Moravec, K., Harvey, R.W., Bangham, J.A.,
Scale trees for stereo vision,
VISP(147), No. 4, 2000, pp. 363-375. 0010
BibRef

Moravec, K.[Kimberly], Harvey, R.W.[Richard W.], Bangham, J.A.[J. Andrew], Fisher, M.H.[Mark H.],
Using an Image Tree to Assist Stereo Matching,
ICIP99(I:26-30).
IEEE DOI BibRef 9900

Bangham, J.A., Moravec, K., Harvey, R.W.,
Scale-Space Trees and Applications as Filters for Stereo Vision and Image Retrieval,
BMVC99(Image Matching and Retrieval).
PDF File. BibRef 9900

Moravec, K., Harvey, R.W., Bangham, J.A.,
Improving Stereo Performance in Regions of Low Texture,
BMVC98(xx-yy). BibRef 9800

Boykov, Y.Y.[Yuri Y.], Veksler, O.[Olga], Zabih, R.[Ramin],
Fast Approximate Energy Minimization via Graph Cuts,
PAMI(23), No. 11, November 2001, pp. 1222-1239.
IEEE DOI 0112
BibRef
Earlier: ICCV99(377-384).
IEEE DOI Award, ICCV Test of Time. BibRef
Earlier:
Disparity Component Matching for Visual Correspondence,
CVPR97(470-475).
IEEE DOI 9704
Dense correspondence, use connected disparity regions. In assigning a disparity at every pixel the smoothness constraint and sharp discontinuities collide. The exact solution is NPhard so find an approximation.
See also What Energy Functions Can Be Minimized via Graph Cuts?.
See also Interactive Graph Cuts for Optimal Boundary and Region Segmentation of Objects in N-D Images.
See also PALMS Image Partitioning: A New Parallel Algorithm for the Piecewise Affine-Linear Mumford-Shah Model. BibRef

Veksler, O.[Olga],
Dense Features for Semi-Dense Stereo Correspondence,
IJCV(47), No. 1-3, April-June 2002, pp. 247-260.
DOI Link 0203
BibRef
Earlier:
Semi-Dense Stereo Correspondence with Dense Features,
CVPR01(II:490-497).
IEEE DOI 0110
BibRef
And: SMBV01(xx-yy). 0110
Connected set of pixels whose boundary points are matched.
See also Stereo Correspondence with Compact Windows via Minimum Ratio Cycle. BibRef

Veksler, O.[Olga],
Multi-label Moves for MRFs with Truncated Convex Priors,
IJCV(98), No. 1, May 2012, pp. 1-14.
WWW Link. 1204
BibRef
Earlier: EMMCVPR09(1-13).
Springer DOI 0908
BibRef
Earlier:
Graph Cut Based Optimization for MRFs with Truncated Convex Priors,
CVPR07(1-8).
IEEE DOI 0706
BibRef
Earlier:
Reducing Search Space for Stereo Correspondence with Graph Cuts,
BMVC06(II:709).
PDF File. 0609
BibRef
Earlier:
Extracting dense features for visual correspondence with graph cuts,
CVPR03(I: 689-694).
IEEE DOI 0307
BibRef

Veksler, O.[Olga],
Stereo Correspondence by Dynamic Programming on a Tree,
CVPR05(II: 384-390).
IEEE DOI 0507
BibRef

Veksler, O.[Olga],
Efficient Graph Cut Optimization for Full CRFs with Quantized Edges,
PAMI(42), No. 4, April 2020, pp. 1005-1012.
IEEE DOI 2003
Image edge detection, Labeling, Inference algorithms, Computational modeling, Optimization methods, fully connected CRFs BibRef

Felzenszwalb, P.F.[Pedro F.], Veksler, O.[Olga],
Tiered scene labeling with dynamic programming,
CVPR10(3097-3104).
IEEE DOI Video of talk:
WWW Link. 1006
Apply DP for pixel labeling with hierarchical structure. BibRef

Felzenszwalb, P.F.[Pedro F.], Pap, G.[Gyula], Tardos, E.[Eva], Zabih, R.[Ramin],
Globally optimal pixel labeling algorithms for tree metrics,
CVPR10(3153-3160).
IEEE DOI 1006
BibRef

Delong, A.[Andrew], Boykov, Y.Y.[Yuri Y.],
A Scalable graph-cut algorithm for N-D grids,
CVPR08(1-8).
IEEE DOI 0806
BibRef

di Stefano, L.[Luigi], Marchionni, M.[Massimiliano], Mattoccia, S.[Stefano],
A Fast Area-Based Stereo Matching Algorithm,
IVC(22), No. 12, 1 October 2004, pp. 983-1005.
Elsevier DOI 0409
BibRef
Earlier: Add A4: Neri, G.[Giovanni], VI02(146).
PDF File. 0208
Reject matches when more reliable matches are found. BibRef

Mattoccia, S.[Stefano],
Accurate Dense Stereo by Constraining Local Consistency on Superpixels,
ICPR10(1832-1835).
IEEE DOI 1008
BibRef

di Stefano, L.[Luigi], Marchionni, M.[Massimiliano], Mattoccia, S.[Stefano], Neri, O.,
Dense stereo based on the uniqueness constraint,
ICPR02(III: 657-661).
IEEE DOI 0211
BibRef

di Stefano, L.[Luigi], Mattoccia, S.[Stefano], Neri, G., Piccinni, D.,
Temporal filtering of disparity measurements,
CIAP01(145-150).
IEEE DOI 0210
BibRef

Tombari, F.[Federico], Mattoccia, S.[Stefano], di Stefano, L.[Luigi], Addimanda, E.[Elisa],
Near real-time stereo based on effective cost aggregation,
ICPR08(1-4).
IEEE DOI 0812
BibRef
And:
Classification and evaluation of cost aggregation methods for stereo correspondence,
CVPR08(1-8).
IEEE DOI 0806
BibRef

Tombari, F.[Federico], di Stefano, L.[Luigi], Mattoccia, S.[Stefano], Mainetti, A.,
A 3D reconstruction system based on improved spacetime stereo,
ICARCV10(1886-1893).
IEEE DOI 1109
BibRef

Mattoccia, S.[Stefano],
Stereo Vision Algorithms for FPGAs,
ECVW13(636-641)
IEEE DOI 1309
3D; FPGA; dense stereo; matching; stereo vision BibRef

Poggi, M.[Matteo], Tosi, F.[Fabio], Mattoccia, S.[Stefano],
Learning a confidence measure in the disparity domain from O(1) features,
CVIU(193), 2020, pp. 102905.
Elsevier DOI 2003
BibRef
Earlier: A1, A3, Only:
Learning a General-Purpose Confidence Measure Based on O(1) Features and a Smarter Aggregation Strategy for Semi Global Matching,
3DV16(509-518)
IEEE DOI 1701
Stereo matching, Confidence measure, Machine learning, Semi global matching BibRef

Aleotti, F.[Filippo], Tosi, F.[Fabio], Ramirez, P.Z.[Pierluigi Zama], Poggi, M.[Matteo], Salti, S.[Samuele], Mattoccia, S.[Stefano], di Stefano, L.[Luigi],
Neural Disparity Refinement for Arbitrary Resolution Stereo,
3DV21(207-217)
IEEE DOI 2201
Performance evaluation, Image resolution, Refining, Neural networks, Computer architecture BibRef

Poggi, M.[Matteo], Aleotti, F.[Filippo], Tosi, F.[Fabio], Zaccaroni, G.[Giulio], Mattoccia, S.[Stefano],
Self-adapting Confidence Estimation for Stereo,
ECCV20(XXIV:715-733).
Springer DOI 2012
BibRef

Tombari, F.[Federico], Mattoccia, S.[Stefano], di Stefano, L.[Luigi],
Stereo for robots: Quantitative evaluation of efficient and low-memory dense stereo algorithms,
ICARCV10(1231-1238).
IEEE DOI 1109
BibRef
Earlier:
Segmentation-Based Adaptive Support for Accurate Stereo Correspondence,
PSIVT07(427-438).
Springer DOI 0712
BibRef

Mattoccia, S.[Stefano],
Fast locally consistent dense stereo on multicore,
ECVW10(69-76).
IEEE DOI 1006
BibRef

Mattoccia, S.[Stefano],
A locally global approach to stereo correspondence,
3DIM09(1763-1770).
IEEE DOI 0910
BibRef

Mattoccia, S.[Stefano], Giardino, S.[Simone], Gambini, A.[Andrea],
Accurate and Efficient Cost Aggregation Strategy for Stereo Correspondence Based on Approximated Joint Bilateral Filtering,
ACCV09(II: 371-380).
Springer DOI 0909
BibRef

Bleyer, M.[Michael], Gelautz, M.[Margrit],
A layered stereo matching algorithm using image segmentation and global visibility constraints,
PandRS(59), No. 3, May 2005, pp. 128-150.
Elsevier DOI 0509
Award, ISPRS. BibRef
Earlier:
A layered stereo algorithm using image segmentation and global visibility constraints,
ICIP04(V: 2997-3000).
IEEE DOI 0505
BibRef

Bleyer, M.[Michael], Gelautz, M.[Margrit],
Graph-cut-based stereo matching using image segmentation with symmetrical treatment of occlusions,
SP:IC(22), No. 2, February 2007, pp. 127-143.
Elsevier DOI 0704
Stereo matching; Segmentation-based matching; Graph-cuts; Occlusion problem BibRef

Bleyer, M.[Michael], Rhemann, C.[Christoph], Gelautz, M.[Margrit],
Segmentation-Based Motion with Occlusions Using Graph-Cut Optimization,
DAGM06(465-474).
Springer DOI 0610
BibRef

Bleyer, M.[Michael], Rother, C.[Carsten], Kohli, P.[Pushmeet], Scharstein, D.[Daniel], Sinha, S.N.[Sudipta N.],
Object stereo: Joint stereo matching and object segmentation,
CVPR11(3081-3088).
IEEE DOI 1106
BibRef

Ogale, A.S.[Abhijit S.], Aloimonos, Y.[Yiannis],
Shape and the Stereo Correspondence Problem,
IJCV(65), No. 3, December 2005, pp. 147-162.
Springer DOI or:
PDF File. 0601
Code, Stereo. BibRef
Earlier:
Robust contrast invariant stereo correspondence,
CRA05(xx-yy).
PDF File. BibRef
The influence of shape on image correspondence,
3DPVT04(945-952).
IEEE DOI 0412
BibRef
And:
Stereo Correspondence with Slanted Surfaces: Critical Implications of Horizontal Slant,
CVPR04(I: 568-573).
IEEE DOI Or:
PDF File. 0408
Related code is also available:
HTML Version. BibRef

Manizade, K.F., Spinhirne, J.D., Lancaster, R.S.,
Stereo Cloud Heights From Multispectral IR Imagery via Region-of-Interest Segmentation,
GeoRS(44), No. 9, September 2006, pp. 2481-2491.
IEEE DOI 0609
BibRef

El Ansari, M.[Mohamed], Masmoudi, L.[Lhoussaine], Bensrhair, A.[Abdelaziz],
A new regions matching for color stereo images,
PRL(28), No. 13, 1 October 2007, pp. 1679-1687.
Elsevier DOI 0709
Stereo vision; Region matching; Color stereo images BibRef

Wang, D.[Daolei], Lim, K.B.[Kah Bin],
Obtaining depth map from segment-based stereo matching using graph cuts,
JVCIR(22), No. 4, May 2011, pp. 325-331.
Elsevier DOI 1104
Stereo matching; Color segmentation; Graph cuts; Disparity plane fitting; Clustering; Optimization; Occlusion; Similarity measure Segement the reference image and use these in matching. BibRef

Haller, I., Nedevschi, S.,
Design of Interpolation Functions for Subpixel-Accuracy Stereo-Vision Systems,
IP(21), No. 2, February 2012, pp. 889-898.
IEEE DOI 1201
BibRef

Qin, X., Shen, J., Mao, X., Li, X., Jia, Y.,
Structured-Patch Optimization for Dense Correspondence,
MultMed(17), No. 3, March 2015, pp. 295-306.
IEEE DOI 1502
Algorithm design and analysis BibRef

Raghavendra, U., Makkithaya, K.[Krishnamoorthi], Karunakar, A.K.,
Anchor-diagonal-based shape adaptive local support region for efficient stereo matching,
SIViP(9), No. 4, May 2015, pp. 893-901.
Springer DOI 1504
BibRef

Li, L., Zhang, S., Yu, X., Zhang, L.,
PMSC: PatchMatch-Based Superpixel Cut for Accurate Stereo Matching,
CirSysVideo(28), No. 3, March 2018, pp. 679-692.
IEEE DOI 1804
computational complexity, graph theory, image matching, image resolution, image segmentation, neural nets, superpixel cut (SC) BibRef

Lim, J.[Jaeseung], Lee, S.[Sankeun],
Patchmatch-Based Robust Stereo Matching Under Radiometric Changes,
PAMI(41), No. 5, May 2019, pp. 1203-1212.
IEEE DOI 1904
Radiometry, Computed tomography, Image color analysis, Robustness, Cost function, Transforms, convex plane refinement BibRef

Hanif, M.S.[Muhammad Shehzad],
Patch match networks: Improved two-channel and Siamese networks for image patch matching,
PRL(120), 2019, pp. 54-61.
Elsevier DOI 1904
Convolutional neural networks, Similarity learning, Local descriptors learning, Patch verification, Patch retrieval BibRef

Pemasiri, A.[Akila], Thanh, K.N.[Kien Nguyen], Sridharan, S.[Sridha], Fookes, C.[Clinton],
Sparse over-complete patch matching,
PRL(122), 2019, pp. 1-6.
Elsevier DOI 1904
Image patch matching, Sparse coding, Neural network BibRef

Tian, M.[Mao], Yang, B.S.[Bi-Sheng], Chen, C.[Chi], Huang, R.G.[Rong-Gang], Huo, L.[Liang],
HPM-TDP: An efficient hierarchical PatchMatch depth estimation approach using tree dynamic programming,
PandRS(155), 2019, pp. 37-57.
Elsevier DOI 1908
Dense depth information from a pair of stereo images. Depth estimation, Stereo matching, Continuous energy optimization, Tree dynamic programming (TDP) BibRef

Song, X.[Xiao], Zhao, X.[Xu], Fang, L.J.[Liang-Ji], Hu, H.[Hanwen], Yu, Y.Z.[Yi-Zhou],
EdgeStereo: An Effective Multi-task Learning Network for Stereo Matching and Edge Detection,
IJCV(128), No. 4, April 2020, pp. 910-930.
Springer DOI 2004
Disparity issues with textureless regions and near boundaries. Use features -- corners, edges, etc. BibRef

Zhang, X.H.[Xiao-Hong], Chen, Y.[Yi], Zhang, H.F.[Hao-Feng], Wang, S.H.[Shui-Hua], Lu, J.F.[Jian-Feng], Yang, J.Y.[Jing-Yu],
When Visual Disparity Generation Meets Semantic Segmentation: A Mutual Encouragement Approach,
ITS(22), No. 3, March 2021, pp. 1853-1867.
IEEE DOI 2103
Semantics, Task analysis, Image segmentation, Estimation, Image resolution, Visualization, Convolution, Scene parsing, mutual encouragement network (MENet) BibRef

Hua, S.Y.[Sheng-You], Sun, Z.Y.[Zhi-Yong], Song, B.[Bo], Liang, P.P.[Peng-Peng], Cheng, E.[Erkang],
Pseudo Segmentation for Semantic Information-Aware Stereo Matching,
SPLetters(29), 2022, pp. 837-841.
IEEE DOI 2204
Costs, Semantics, Feature extraction, Image segmentation, Task analysis, Correlation, Deep learning, stereo matching, pseudo segmenta- tion BibRef

Rouabhia, D.[Djaber], Djedi, N.E.[Nour Eddine],
A combination of 'feature mapping' and 'block' approaches to reduce the matching area of stereoscopic algorithms,
IJCVR(13), No. 6, 2023, pp. 641-657.
DOI Link 2310
BibRef

Cheng, J.[Junda], Yang, X.[Xin], Pu, Y.[Yuechuan], Guo, P.[Peng],
Region Separable Stereo Matching,
MultMed(25), 2023, pp. 4880-4893.
IEEE DOI 2311
BibRef

Ai, X.D.[Xin-Dong], Yang, Z.[Zuliu], Yang, W.[Weida], Zhao, Y.[Yong], Yu, Z.Z.[Zheng-Zhong], Li, F.[Fuchi],
Suppressing Features That Contain Disparity Edge For Stereo Matching,
ICPR21(7985-7991)
IEEE DOI 2105
Convolution, Image edge detection, Aggregates, Feature extraction BibRef

Gee, T.[Trevor], Delmas, P.[Patrice],
Reconstruction with Guided PatchMatch Stereo,
MVA19(1-6)
DOI Link 1911
dynamic programming, image matching, image reconstruction, stereo image processing, Earth BibRef

Khamis, S.[Sameh], Fanello, S.[Sean], Rhemann, C.[Christoph], Kowdle, A.[Adarsh], Valentin, J.[Julien], Izadi, S.[Shahram],
StereoNet: Guided Hierarchical Refinement for Real-Time Edge-Aware Depth Prediction,
ECCV18(XV: 596-613).
Springer DOI 1810
BibRef

Chabra, R.[Rohan], Straub, J.[Julian], Sweeney, C.[Christopher], Newcombe, R.A.[Richard A.], Fuchs, H.[Henry],
StereoDRNet: Dilated Residual StereoNet,
CVPR19(11778-11787).
IEEE DOI 2002
BibRef

Yang, G.R.[Guo-Run], Zhao, H.S.[Heng-Shuang], Shi, J.P.[Jian-Ping], Deng, Z.D.[Zhi-Dong], Jia, J.Y.[Jia-Ya],
SegStereo: Exploiting Semantic Information for Disparity Estimation,
ECCV18(VII: 660-676).
Springer DOI 1810
BibRef

Chen, B., Jung, C.,
Patch-Based Stereo Matching Using 3D Convolutional Neural Networks,
ICIP18(3633-3637)
IEEE DOI 1809
Color, Image edge detection, Image color analysis, Training, Convolutional neural networks, patch-based BibRef

Quenneville, D., Scharstein, D.[Daniel],
Mondrian stereo,
ICIP17(136-140)
IEEE DOI 1803
Cognition, Image color analysis, Image edge detection, Image segmentation, Merging, Surface treatment, untextured scenes BibRef

Liu, J.L.[Jiao-Li], Zhang, L.F.[Lin-Feng], Tao, J.[Jia],
A joint stereo matching in the pixel and image level,
ICIVC17(138-144)
IEEE DOI 1708
Correlation, Image color analysis, Image segmentation, Interpolation, Reliability, Surface fitting, adaptive support, bundle constrains, stereo matching, surface, interpolation BibRef

Drouyer, S.[Sébastien], Beucher, S.[Serge], Bilodeau, M.[Michel], Moreaud, M.[Maxime], Sorbier, L.[Loïc],
Sparse Stereo Disparity Map Densification Using Hierarchical Image Segmentation,
ISMM17(172-184).
Springer DOI 1706
BibRef

Li, A.[Ang], Chen, D.P.[Da-Peng], Liu, Y.L.[Yuan-Liu], Yuan, Z.J.[Ze-Jian],
Coordinating Multiple Disparity Proposals for Stereo Computation,
CVPR16(4022-4030)
IEEE DOI 1612
Stereo, large textureless regions. BibRef

Wu, W., Li, L., Jin, W.,
Disparity refinement based on segment-tree and fast weighted median filter,
ICIP16(3449-3453)
IEEE DOI 1610
Decision support systems BibRef

Veldandi, M.[Muninder], Ukil, S.[Soumik], Govindarao, K.[Krishna],
Robust segment-based Stereo using Cost Aggregation,
BMVC14(xx-yy).
HTML Version. 1410
BibRef

Ghosh, P.[Pallabi], Venkatesh, K.S.,
Fast and efficient computation of stereo depth maps,
3DTV-CON13(1-4)
IEEE DOI 1309
DAISY;SIFT;Stereo vision;depth discontinuities;graph cuts BibRef

Howard, J.[Joel], Morse, B.S.[Bryan S.], Cohen, S.[Scott], Price, B.L.[Brian L.],
Depth-based patch scaling for content-aware stereo image completion,
WACV14(9-16)
IEEE DOI 1406
BibRef
Earlier: A2, A1, A3, A4:
PatchMatch-Based Content Completion of Stereo Image Pairs,
3DIMPVT12(555-562).
IEEE DOI 1212
Boolean functions BibRef

Zheng, Y.[Ying], Gu, S.[Steve], Tomasi, C.[Carlo],
Fast Tiered Labeling with Topological Priors,
ECCV12(IV: 587-601).
Springer DOI 1210
Vertical order (sky ground) BibRef

Klowsky, R.[Ronny], Kuijper, A.[Arjan], Goesele, M.[Michael],
Modulation transfer function of patch-based stereo systems,
CVPR12(1386-1393).
IEEE DOI 1208
BibRef

Brewer, N., Liu, N., Wang, L.,
Stereo disparity calculation in real-world scenes with Informative Image Partitioning,
IVCNZ10(1-8).
IEEE DOI 1203
BibRef

Sidhu, H.S.[Harkanwal Singh], Kumar, S.[Satish], Das, A.[Amitava], Sardana, H.K.,
A robust area based disparity estimation technique for stereo vision applications,
ICIIP11(1-4).
IEEE DOI 1112
BibRef

Dai, X.B.[Xian-Biao], Wang, L.[Liang], Cui, P.Y.[Ping-Yuan],
An improved region-growth algorithm for disparity estimation,
IASP10(411-414).
IEEE DOI 1004
BibRef

Wang, G.C.[Gui-Cai], Wang, L.[Liang], Cui, P.Y.[Ping-Yuan],
A Stereo Matching Algorithm Based on Image Segmentation and Features Point,
CISP09(1-5).
IEEE DOI 0910
BibRef

Wang, Z.F.[Zeng-Fu], Zheng, Z.G.[Zhi-Gang],
A region based stereo matching algorithm using cooperative optimization,
CVPR08(1-8).
IEEE DOI 0806
BibRef

Zhou, X.Z.[Xiu-Zhi], Wang, R.S.[Run-Sheng],
Symmetric Pixel-Group Based Stereo Matching for Occlusion Handling,
ICPR06(I: 47-50).
IEEE DOI 0609
Segement images on color and disparity and the regions in the other image. BibRef

Sun, J.[Jian], Li, Y.[Yin], Kang, S.B.[Sing Bing], Shum, H.Y.[Heung-Yeung],
Symmetric Stereo Matching for Occlusion Handling,
CVPR05(II: 399-406).
IEEE DOI 0507
Symmetry. BibRef

Delponte, E.[Elisabetta], Isgrò, F.[Francesco], Odone, F.[Francesca], Verri, A.[Alessandro],
Large Baseline Matching of Scale Invariant Features,
CIAP05(794-801).
Springer DOI 0509
BibRef

McKinnon, B.[Brian], Baltes, J.[Jacky],
Fast Line-Segment Extraction for Semi-dense Stereo Matching,
RobVis08(59-71).
Springer DOI 0802
BibRef

McKinnon, B.[Brian], Baltes, J.[Jacky],
Practical Region-Based Matching for Stereo Vision,
IWCIA04(726-738).
Springer DOI 0505
BibRef

Egnal, G.[Geoffrey], Mintz, M.[Max], Daniilidis, K.[Kostas],
Limiting the Search Range of Correlation Stereo Using Silhouettes,
VI02(170).
PDF File. 0208
BibRef

Zhang, Y., Kambhamettu, C.,
Stereo Matching with Segmentation-Based Cooperation,
ECCV02(II: 556 ff.).
Springer DOI 0205
BibRef

Tarel, J.P., and Vezien, J.M.,
A generic approach for planar patches stereo reconstruction,
SCIA95(II: 1061-1070). Regions are matched with distortions. Segment regions first. BibRef 9500

Tao, H.[Hai], Sawhney, H.S.[Harpreet S.], Kumar, R.[Rakesh],
A Global Matching Framework for Stereo Computation,
ICCV01(I: 532-539).
IEEE DOI 0106
BibRef

Tao, H.[Hai], Sawhney, H.S.[Harpreet S.],
Global Matching Criterion and Color Segmentation Based Stereo,
WACV00(246-253).
IEEE DOI 0010
Stereo analysis. Regions help the analysis. Compute depth. Warp (re-render, view based rendering) according to depth, copmare to iamge. Allow depth discontinuities at region boundaries. Very clean results. BibRef

Silva, C., Santos-Victor, J.,
Intrinsic Images for Dense Stereo Matching with Occlusions,
ECCV00(I: 100-114).
Springer DOI 0003
BibRef

Vestri, C.[Christoph], Devernay, F.[Frederic],
Improving Correlation-based DEMs by Image Warping and Facade Correlation,
CVPR00(I: 438-443).
IEEE DOI 0005
improve DEM by adding edge info BibRef

Morris, D.D.[Daniel D.], Kanade, T.[Takeo],
Image-Consistent Surface Triangulation,
CVPR00(I: 332-338).
IEEE DOI 0005
Refine stero model using surfaces BibRef

Maas, R.[Robert], ter Haar Romeny, B.M.[Bart M.], Viergever, M.A.[Max A.],
Area-Based Computation of Stereo Disparity with Model-Based Window Size Selection,
CVPR99(I: 106-112).
IEEE DOI BibRef 9900

Wei, G.Q.[Guo-Qing], and Hirzinger, G.[Gerd],
Intensity and Feature Based Stereo Matching by Disparity Parametrization,
ICCV98(1035-1040).
IEEE DOI BibRef 9800

Fusiello, A., Roberto, V., Trucco, E.,
Efficient Stereo with Multiple Windowing,
CVPR97(858-863).
IEEE Abstract.
IEEE DOI 9704
BibRef
And:
Experiments with a new area-based stereo algorithm,
CIAP97(I: 669-676).
Springer DOI 9709
To deal with occlusions. BibRef

Sara, R., Bajcsy, R.,
On Occluding Contour Artifacts in Stereo Vision,
CVPR97(852-857).
IEEE Abstract.
IEEE DOI 9704
Step edges cause problems in stereo. BibRef

Wiman, H.,
Automatic Generation of Digital Surface Models Through Matching in Object Space,
SSAB97(Photogrammetry) 9703
BibRef

Liu, J., and Huang, S.,
Using Topological Information of Images to Improve Stereo Matching,
CVPR93(653-654).
IEEE DOI BibRef 9300

Chapter on Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular continues in
Stereo and Surface Models .