Moravec, H.,
Rover Visual Obstacle Avoidance,
IJCAI81(785-790).
BibRef
8100
Earlier:
Visual Mapping by Robot Rover,
IJCAI79(598-600).
BibRef
And:
Towards Automatic Visual Obstacle Avoidance,
IJCAI77(584).
Interest Operator, Moravec. There is no real published reference. These papers are
important for two ideas, first using multiple resolution images to improve the
speed in matching, and second using an interest operator to locate points to be
used in the matching. The correlation based matcher is used to find the best
match for each of the "interesting" points in one image. First the image is
reduced and the resulting images are used. This gives an approximate location
for the corresponding point in the second image. The next higher resolution
images then are used to refine the match locations, but the search space for
the exact match has been reduced to the area around the location at the lower
resolution.
Correlation based matching.
See also Stanford Cart and the CME Rover, The.
BibRef
Moravec, H.,
Obstacle Avoidance and Navigation in the Real World
by a Seeing Robot Rover,
Ph.D.Thesis (CS), 1980.
BibRef
8000
Stanford AIMemo 340
and
BibRef
STAN-CS-80-813.
BibRef
And:
CMU-RI-TR-3, 1980.
The complete thesis.
BibRef
Moravec, H.P.[Hans P.],
Robot Rover Visual Navigation,
UMI Research PressAnn Arbor, MI, 1981.
The printed book from the thesis.
BibRef
8100
Barnard, S.T.,
Stochastic Stereo Matching over Scale,
IJCV(3), No. 1. May 1989, pp. 17-32.
Springer DOI
BibRef
8905
IJCV(3), No. 1. May 1989, pp. 17-32.
Springer DOI
BibRef
Earlier:
DARPA88(769-778),
BibRef
Stereo Matching by Hierarchial, Microcanonical Annealing,
IJCAI87(832-835),
BibRef
DARPA87(792-797).
BibRef
And:
A Stochastic Approach to Stereo Vision,
AAAI-86(676-680).
BibRef
And:
RCV87(21-25).
Use the simulated annealing approach to fit a warped
surface over different scales.
BibRef
Barnard, S.T.,
Recent Progress in CYCLOPS: A System for Stereo Cartography,
DARPA90(449-455).
Extensions of his earlier stereo work.
BibRef
9000
Quam, L.H.,
Hierarchical Warp Stereo,
DARPA84(149-155)
BibRef
8400
And:
RCV87(80-86).
PDF File. Generating the global matches based on a warping
function to fill in the gaps between what can really be matched.
BibRef
de Vleeschauwer, D.,
An Intensity-Based, Coarse-to-Fine Approach
to Reliably Measure Binocular Disparity,
CVGIP(57), No. 2, March 1993, pp. 204-218.
DOI Link Estimate the disparities, then eliminate the obvious bad points.
BibRef
9303
Yang, Y.B.[Yi-Bing],
Yuille, A.L.,
Multilevel Enhancement and Detection of Stereo Disparity Surfaces,
AI(78), No. 1-2, October 1995, pp. 121-145.
Elsevier DOI spatio-disparity space. Find a good surface.
BibRef
9510
Yang, Y.B.[Yi-Bing],
Yuille, A.L.,
Lu, J.,
Local, Global, and Multilevel Stereo Matching,
CVPR93(274-279).
IEEE DOI A distinction is made between multi-level and multi-resolution matching.
BibRef
9300
Marapane, S.B.,
Trivedi, M.M.[Mohan M.],
Multi-Primitive Hierarchical (MPH) Stereo System,
PAMI(16), No. 3, March 1994, pp. 227-240.
IEEE DOI
BibRef
9403
Earlier:
CVPR92(499-505).
IEEE DOI
BibRef
And:
An Active Vision System for Multi-Primitive Hierarchical Stereo Analysis
and Multi-Cue Depth Extraction,
SPIE(1956), Sensor Fusion Conference, Orlando, FL, April 1993.
Does use some regions in a match and line segments then individual
edgels for details. Generates disparity maps, not surfaces.
BibRef
Marapane, S.B.,
Trivedi, M.M.[Mohan M.],
Region-Based Stereo Analysis for Robotic Applications,
SMC(19), No. 6, November/December 1989, pp. 1447-1464.
Stereo using regions to generate coarse disparity maps.
Graph matching using region features only.
See also Vision System for Robotic Inspection and Manipulation, A.
BibRef
8911
Marapane, S.B.,
Trivedi, M.M.[Mohan M.],
Region and Edge Segment Based Stereo Analysis,
SPIE(1571), International Symposium on Intelligent Robotics,
Bangalore, India, January 1991, pp. 71-82.
BibRef
9101
Earlier:
Edge Segment Based Stereo Analysis,
SPIE(1293), Applications of AI VIII, Orlando, FL, April 1990,
pp. 140-151.
BibRef
Marapane, S.B.,
Trivedi, M.M.[Mohan M.],
Extracting Depth by Binocular Stereo in a Robot Vision System,
SPIE(1012), Applications of Digital Image Processing XI,
San Diego, CA, August 1988.
BibRef
8808
Kim, D.H.,
Koo, K.B.,
Choi, W.Y.,
Park, R.H.,
Stereo Matching Using Hierarchical Features for Robotic Applications,
AdvRob(10), No. 1, 1996, pp. 1-14.
BibRef
9600
Lacey, A.J.,
Thacker, N.A.,
Crossley, S.,
Yates, R.B.,
A Multistage Approach to the Dense Estimation of
Disparity from Stereo SEM Images,
IVC(16), No. 5, April 27 1998, pp. 373-383.
Elsevier DOI
9805
BibRef
Earlier: A1, A2, A4, Only:
Surface Approximation from Industrial SEM Images,
BMVC96(Applications).
9608
scanning electron microscope images.
University of Sheffield
BibRef
Crossley, S.,
Lacey, A.J.,
Thacker, N.A.,
Seed, N.L.,
Robust Stereo via Temporal Consistency,
BMVC97(xx-yy).
HTML Version.
0209
BibRef
Crossley, S.,
Thacker, N.A.,
Seed, N.L.,
Benchmarking of Bootstrap Temporal Stereo using
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BibRef
9800
Crossley, S.,
Seed, N.L.,
Thacker, N.A.,
Ivey, P.A.,
Improving accuracy, robustness and computational efficiency in 3D
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Elsevier DOI
0403
Extend stereo analysis with robust techniques.
BibRef
Wang, Y., and
Bhattacharya, P.,
Hierarchical Stereo Correspondence Using Features of Gray Connected Components,
MGV(8), No. 1, 1999, pp. 19-54.
BibRef
9900
Earlier:
ICIP97(III: 264-267).
IEEE DOI
See also On Parameter-Dependent Connected Components of Gray Images.
BibRef
Melen, R.D.[Roger D.],
Disparity measurement with variably sized interrogation regions,
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And:
Compensating pixel records of related images for detecting images disparity, apparatus and method,
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Neumann, J.[Jan],
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Spatio-Temporal Stereo Using Multi-Resolution Subdivision Surfaces,
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DOI Link
0203
BibRef
Neumann, J.[Jan],
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Multi-Modality Stereo with Varying Spatial, Temporal, and Spectral
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SMBV01(xx-yy).
0110
BibRef
Alvarez, L.[Luis],
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Weickert, J.[Joachim],
Dense Disparity Map Estimation Respecting Image Discontinuities:
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0204
BibRef
Earlier:
INRIARR-3874, January 2000.
HTML Version.
0105
See also Reliable Estimation of Dense Optical Flow Fields with Large Displacements.
BibRef
Alvarez, L.[Luis],
Deriche, R.[Rachid],
Santana, F.[Francisco],
Recursivity and PDE's in Image Processing,
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IEEE DOI
0009
BibRef
Yokoyama, A.[Atsushi],
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0806
BibRef
Earlier:
Multiscale Image Disparity Estimation using the Quaternion Wavelet
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ICIP06(1229-1232).
IEEE DOI
0610
BibRef
Min, D.B.[Dong-Bo],
Sohn, K.H.[Kwang-Hoon],
Cost Aggregation and Occlusion Handling With WLS in Stereo Matching,
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IEEE DOI
0808
BibRef
Min, D.B.[Dong-Bo],
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1309
BibRef
Earlier:
A revisit to cost aggregation in stereo matching:
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ICCV11(1567-1574).
IEEE DOI
1201
Accuracy.
BibRef
Ham, B.[Bumsub],
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A Generalized Random Walk With Restart and its Application in Depth Up-Sampling and Interactive Segmentation,
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IEEE DOI
1307
BibRef
Earlier:
Cost aggregation with anisotropic diffusion in feature space for hybrid
stereo matching,
ICIP11(3365-3368).
IEEE DOI
1201
See also Virtual view rendering using super-resolution with multiview images. anisotropic diffusion model; interactive image segmentation;
depth up-sampling
BibRef
Ham, B.[Bumsub],
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1504
directed graphs
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Yun, S.U.[Sang-Un],
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3D Scene Reconstruction System with Hand-Held Stereo Cameras,
3DTV07(1-4).
IEEE DOI
0705
BibRef
Oh, C.[Changjae],
Ham, B.[Bumsub],
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Probabilistic Correspondence Matching using Random Walk with Restart,
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DOI Link
1301
BibRef
Yoon, S.U.[Sang-Un],
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Fast Dense Stereo Matching Using Adaptive Window in Hierarchical
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ISVC06(II: 316-325).
Springer DOI
0611
Given initial disparity, find edges.
Improve using these edges.
BibRef
Poli, D.[Daniela],
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1211
BibRef
Earlier:
Refinement of Digital Surface Models through Constrained Connectivity
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HighRes11(xx-yy).
PDF File.
1106
BibRef
Brunton, A.[Alan],
Lang, J.[Jochen],
Dubois, E.[Eric],
Efficient Multi-scale Stereo of High-Resolution Planar and Spherical
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3DIMPVT12(120-127).
IEEE DOI
1212
BibRef
Sandoz, P.[Patrick],
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1211
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Yang, Q.Q.[Qing-Qing],
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SPLetters(20), No. 3, March 2013, pp. 237-240.
IEEE DOI
1303
BibRef
Earlier: A1, A3, A2, A4:
Hierarchical Joint Bilateral Filtering for Depth Post-Processing,
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IEEE DOI
1109
To get accurate and smooth depth map. Use depth confidence measures.
BibRef
Yang, Q.Q.[Qing-Qing],
Ji, P.[Pan],
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Yao, S.J.[Shao-Jun],
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IVC(32), No. 3, 2014, pp. 202-211.
Elsevier DOI
1403
Stereo vision
BibRef
Huq, S.[Shafik],
Koschan, A.F.[Andreas F.],
Abidi, M.A.[Mongi A.],
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CVIU(117), No. 6, June 2013, pp. 688-704.
Elsevier DOI
1304
Stereo matching; Occlusion; Probability; Image noise; Clustering
BibRef
Huq, S.[Shafik],
Koschan, A.F.[Andreas F.],
Abidi, B.R.[Besma R.],
Abidi, M.A.[Mongi A.],
Efficient BP stereo with automatic paramemeter estimation,
ICIP08(301-304).
IEEE DOI
0810
Belief propogation stereo.
BibRef
Wang, Y.C.,
Tung, C.P.,
Chung, P.C.,
Efficient Disparity Estimation Using Hierarchical Bilateral Disparity
Structure Based Graph Cut Algorithm With a Foreground Boundary
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IEEE DOI
1305
BibRef
Morales, S.[Sandino],
Klette, R.[Reinhard],
Kalman-filter based spatio-temporal disparity integration,
PRL(34), No. 8, June 2013, pp. 873-883.
Elsevier DOI
1305
BibRef
Earlier:
Spatio-Temporal Stereo Disparity Integration,
CAIP11(II: 540-547).
Springer DOI
1109
BibRef
And:
A Third Eye for Performance Evaluation in Stereo Sequence Analysis,
CAIP09(1078-1086).
Springer DOI
0909
Stereo algorithms; Kalman filter; Disparity propagation; Spatial
domain; Temporal domain; Vision-based driver assistance
BibRef
Morales, S.[Sandino],
Penc, J.[Joachim],
Vaudrey, T.[Tobi],
Klette, R.[Reinhard],
Graph-Cut versus Belief-Propagation Stereo on Real-World Images,
CIARP09(732-740).
Springer DOI
0911
BibRef
Tao, R.S.[Rong-Shu],
Xiang, Y.M.[Yu-Ming],
You, H.J.[Hong-Jian],
An Edge-Sense Bidirectional Pyramid Network for Stereo Matching of
VHR Remote Sensing Images,
RS(12), No. 24, 2020, pp. xx-yy.
DOI Link
2012
BibRef
Xia, Y.X.[Yuan-Xin],
d'Angelo, P.[Pablo],
Fraundorfer, F.[Friedrich],
Tian, J.J.[Jiao-Jiao],
Reyes, M.F.[Mario Fuentes],
Reinartz, P.[Peter],
GA-Net-Pyramid: An Efficient End-to-End Network for Dense Matching,
RS(14), No. 8, 2022, pp. xx-yy.
DOI Link
2205
BibRef
He, S.[Sheng],
Li, S.H.[Shen-Hong],
Jiang, S.[San],
Jiang, W.S.[Wan-Shou],
HMSM-Net: Hierarchical multi-scale matching network for disparity
estimation of high-resolution satellite stereo images,
PandRS(188), 2022, pp. 314-330.
Elsevier DOI
2205
Satellite stereo images, Disparity estimation,
Convolutional neural network, GaoFen-7 dataset
BibRef
Yang, X.W.[Xiao-Wei],
Zhao, Y.[Yong],
Feng, Z.G.[Zhi-Guo],
Sang, H.W.[Hai-Wei],
Zhang, Z.B.[Zhen-Bo],
Zhang, G.Y.[Gui-Ying],
He, L.[Lin],
A light-weight stereo matching network based on multi-scale features
fusion and robust disparity refinement,
IET-IPR(17), No. 6, 2023, pp. 1797-1811.
DOI Link
2305
image processing, stereo image processing
BibRef
Zhu, Z.Y.[Zi-Yu],
Guo, W.[Wei],
Chen, W.[Wei],
Li, Q.P.[Qiu-Ping],
Zhao, Y.[Yong],
MPANET: Multi-Scale Pyramid Aggregation Network for Stereo Matching,
ICIP21(2773-2777)
IEEE DOI
2201
Image processing, Aggregates, Estimation, stereo matching,
foreground areas, multi-scale pyramid aggregation, pseudo-label
BibRef
Li, P.F.[Peng-Fei],
Ye, S.Q.[Shui-Qiang],
Zhang, J.Q.[Jia-Quan],
Xinan, W.[Wang],
Dai, Q.F.[Qi-Fei],
Yu, Z.Z.[Zheng-Zhong],
Li, F.[Fuchi],
Zhao, Y.[Yong],
Self-adaptive Multi-scale Aggregation Network for Stereo Matching,
ICPR22(3794-3800)
IEEE DOI
2212
Costs, Correlation, Fuses, Volume measurement,
Convolutional neural networks
BibRef
Li, Z.Z.[Zi-Zhuo],
Su, C.B.[Chun-Bao],
Fan, F.[Fan],
Huang, J.[Jun],
Ma, J.Y.[Jia-Yi],
MC-Net: Integrating Multi-Level Geometric Context for Two-View
Correspondence Learning,
CirSysVideo(34), No. 8, August 2024, pp. 7550-7565.
IEEE DOI
2408
Vectors, Feature extraction, Circuits and systems, Fans, Estimation,
Visualization, Transforms, Correspondence learning, outlier rejection
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Tosi, F.[Fabio],
Aleotti, F.[Filippo],
Ramirez, P.Z.[Pierluigi Zama],
Poggi, M.[Matteo],
Salti, S.[Samuele],
Mattoccia, S.[Stefano],
di Stefano, L.[Luigi],
Neural Disparity Refinement,
PAMI(46), No. 12, December 2024, pp. 8900-8917.
IEEE DOI
2411
Feature extraction, Noise measurement, Estimation, Training,
Task analysis, Pipelines, Stereo matching, deep learning, domain generalization
BibRef
Shen, Z.L.[Zhe-Lun],
Dai, Y.C.[Yu-Chao],
Song, X.B.[Xi-Bin],
Rao, Z.B.[Zhi-Bo],
Zhou, D.F.[Ding-Fu],
Zhang, L.J.[Liang-Jun],
PCW-Net: Pyramid Combination and Warping Cost Volume for Stereo
Matching,
ECCV22(XXXII:280-297).
Springer DOI
2211
BibRef
Yang, M.,
Wu, F.,
Li, W.,
WaveletStereo: Learning Wavelet Coefficients of Disparity Map in
Stereo Matching,
CVPR20(12882-12891)
IEEE DOI
2008
Wavelet transforms, Image reconstruction, Estimation,
Image resolution, Signal resolution
BibRef
Saikia, T.,
Marrakchi, Y.,
Zela, A.,
Hutter, F.,
Brox, T.,
AutoDispNet: Improving Disparity Estimation With AutoML,
ICCV19(1812-1823)
IEEE DOI
2004
Bayes methods, encoding, gradient methods,
image classification, learning (artificial intelligence),
Bayes methods
BibRef
Ye, Z.,
Xu, Y.,
Hoegner, L.,
Tong, X.,
Stilla, U.,
Precise Disparity Estimation for Narrow Baseline Stereo Based On
Multiscale Superpixels and Phase Correlation,
Semantics3D19(147-153).
DOI Link
1912
BibRef
Chang, J.,
Chen, Y.,
Pyramid Stereo Matching Network,
CVPR18(5410-5418)
IEEE DOI
1812
Estimation, Convolution,
Biomedical optical imaging, Optical imaging, Semantics, Solid modeling
BibRef
Batsos, K.,
Mordohai, P.,
RecResNet:
A Recurrent Residual CNN Architecture for Disparity Map Enhancement,
3DV18(238-247)
IEEE DOI
1812
convolution, feedforward neural nets, image enhancement,
image matching, image sampling, recurrent neural nets,
stereo matching
BibRef
Weng, J.,
Zhang, W.,
Zhang, W.,
Gao, J.,
Pyramid stereo matching for spherical panoramas,
VCIP16(1-4)
IEEE DOI
1701
Buildings
BibRef
Freundlich, C.[Charles],
Zavlanos, M.[Michael],
Mordohai, P.[Philippos],
Exact bias correction and covariance estimation for stereo vision,
CVPR15(3296-3304)
IEEE DOI
1510
BibRef
Cheng, Y.[Yang],
Matthies, L.H.[Larry H.],
Stereovision Bias Removal by Autocorrelation,
WACV15(1153-1160)
IEEE DOI
1503
Benchmark testing. subpixel interpolation.
BibRef
Murarka, A.[Aniket],
Einecke, N.[Nils],
A Meta-Technique for Increasing Density of Local Stereo Methods
through Iterative Interpolation and Warping,
CRV14(254-261)
IEEE DOI
1406
Benchmark testing
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Kim, J.[Jaechul],
Liu, C.[Ce],
Sha, F.[Fei],
Grauman, K.[Kristen],
Deformable Spatial Pyramid Matching for Fast Dense Correspondences,
CVPR13(2307-2314)
IEEE DOI
1309
BibRef
Zhang, K.[Kang],
Li, J.Y.[Ji-Yang],
Li, Y.J.[Yi-Jing],
Hu, W.D.[Wei-Dong],
Sun, L.F.[Li-Feng],
Yang, S.Q.[Shi-Qiang],
Binary stereo matching,
ICPR12(356-359).
WWW Link.
1302
BibRef
Earlier: A4, A1, A5, A2, A3, A6:
Virtual support window for adaptive-weight stereo matching,
VCIP11(1-4).
IEEE DOI
1201
BibRef
Wang, K.,
Stutts, C.,
Dunn, E.[Enrique],
Frahm, J.M.[Jan-Michael],
Efficient joint stereo estimation and land usage classification for
multiview satellite data,
WACV16(1-9)
IEEE DOI
1606
Cameras
BibRef
Wang, Y.L.[Yi-Lin],
Wang, K.[Ke],
Dunn, E.[Enrique],
Frahm, J.M.[Jan-Michael],
Stereo under Sequential Optimal Sampling:
A Statistical Analysis Framework for Search Space Reduction,
CVPR14(485-492)
IEEE DOI
1409
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Wang, Y.L.[Yi-Lin],
Dunn, E.[Enrique],
Frahm, J.M.[Jan-Michael],
Increasing the Efficiency of Local Stereo by Leveraging Smoothness
Constraints,
3DIMPVT12(246-253).
IEEE DOI
1212
BibRef
Jen, Y.H.[Yi-Hung],
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Fite-Georgel, P.[Pierre],
Frahm, J.M.[Jan-Michael],
Adaptive Scale Selection for Hierarchical Stereo,
BMVC11(xx-yy).
HTML Version.
1110
See also Efficient Generation of Multi-perspective Panoramas.
See also Building Rome on a Cloudless Day.
BibRef
Won, K.H.[Kwang Hee],
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hSGM: Hierarchical Pyramid Based Stereo Matching Algorithm,
ACIVS11(693-701).
Springer DOI
1108
BibRef
Yang, Q.X.[Qing-Xiong],
A non-local cost aggregation method for stereo matching,
CVPR12(1402-1409).
IEEE DOI
1208
BibRef
Yang, Q.X.[Qing-Xiong],
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A constant-space belief propagation algorithm for stereo matching,
CVPR10(1458-1465).
IEEE DOI
1006
BibRef
Sorgi, L.[Lorenzo],
Schlosser, M.[Markus],
Integrating Color Sampling into Depth Based Bilayer Segmentation,
CIAP13(I:31-40).
Springer DOI
1311
BibRef
Jachalsky, J.[Jorn],
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Reliability-aware cross multilateral filtering for robust disparity map
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3DTV10(1-4).
IEEE DOI
1006
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Liu, T.L.[Tian-Liang],
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Dense Stereo Correspondence with Contrast Context Histogram,
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PSIVT09(449-461).
Springer DOI
0901
BibRef
Laureano, G.T.[Gustavo Teodoro],
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Disparities Maps Generation Employing Multi-resolution Analysis and
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IPTA08(1-6).
IEEE DOI
0811
BibRef
Gu, Q.Q.[Quan-Quan],
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A similarity measure under Log-Euclidean metric for stereo matching,
ICPR08(1-4).
IEEE DOI
0812
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And:
Belief propagation on Riemannian manifold for stereo matching,
ICIP08(1788-1791).
IEEE DOI
0810
BibRef
Boughorbel, F.[Faysal],
A New Multiple-Windows Depth from Stereo Algorithm for 3D Displays,
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0705
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Shukla, N.K.[Narendra Kumar],
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An Efficient Adaptive Window Based Disparity Map Computation Algorithm
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ICCVGIP06(894-905).
Springer DOI
0612
BibRef
Kai, Z.[Zhang],
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Hierarchical Stereo Matching: From Foreground to Background,
ACIVS06(632-643).
Springer DOI
0609
BibRef
Nehab, D.[Diego],
Rusinkiewicz, S.[Szymon],
Davis, J.E.[James E.],
Improved Sub-pixel Stereo Correspondences through Symmetric Refinement,
ICCV05(I: 557-563).
IEEE DOI
0510
Not just refinement from coarse match.
BibRef
Tornow, M.,
Michaelis, B.,
Kuhn, R.W.,
Calow, R.,
Mecke, R.,
Hierarchical Method for Stereophotogrammetric Multi-object-position
Measurement,
DAGM03(164-171).
Springer DOI
0310
BibRef
Caspary, G.,
Zeevi, Y.Y.,
Multiresolution approach to three-dimensional stereo vision,
3DPVT02(784-787).
IEEE DOI
0206
BibRef
And:
Wavelet-based multiresolution stereo vision,
ICPR02(III: 680-683).
IEEE DOI
0211
BibRef
Gherardi, R.,
Castellani, U.,
Fusiello, A.,
Murino, V.,
Optimal Parameter Estimation for MRF Stereo Matching,
CIAP05(818-825).
Springer DOI
0509
BibRef
Fusiello, A.[Andrea],
Castellani, U.[Umberto],
Murino, V.[Vittorio],
Relaxing Symmetric Multiple Windows Stereo Using Markov Random Fields,
EMMCVPR01(91-105).
Springer DOI
0205
BibRef
Earlier: A3, A2, A1:
Disparity Map Restoration by Integration of Confidence in Markov Random
Fields Models,
ICIP01(II: 29-32).
IEEE DOI
0108
BibRef
Castellani, U.,
Livatino, S.,
Fisher, R.B.,
Improving environment modelling by edge occlusion surface completion,
3DPVT02(672-675).
IEEE DOI
0206
BibRef
Park, S.Y.[Sang Yoon],
Lee, S.H.[Sang Hwa],
Cho, N.I.[Nam Ik],
Segmentation based disparity estimation using color and depth
information,
ICIP04(V: 3275-3278).
IEEE DOI
0505
BibRef
Lee, S.H.[Sang Hwa],
Cho, N.I.[Nam Ik],
Park, J.I.[Jong-Il],
Disparity estimation using color coherence and stochastic diffusion,
ICIP04(II: 1373-1376).
IEEE DOI
0505
BibRef
And:
Stochastic Diffusion for Correspondence Estimation and Objects
Segmentation,
GenModel04(183).
IEEE DOI
0406
BibRef
Lee, S.H.[Sang Hwa],
Cho, N.I.[Nam Ik],
Kanatsugu, Y.,
Park, J.I.[Jong-Il],
Simultaneous object extraction and disparity estimation using
stochastic diffusion,
ICIP03(III: 457-460).
IEEE DOI
0312
BibRef
Lee, S.H.[Sang Hwa],
Park, S.Y.[Sang Yoon],
Cho, N.I.[Nom Ik],
Kanatsugu, Y.,
Park, J.I.[Jong-Il],
Occlusion detection and stereo matching in a stochastic method,
ICIP03(I: 377-380).
IEEE DOI
0312
BibRef
Lee, S.H.[Sang Hwa],
Kanatsugu, Y.,
Park, J.I.[Jong-Il],
A hierarchical method of map-based stochastic diffusion and disparity
estimation,
ICIP02(II: 541-544).
IEEE DOI
0210
BibRef
Lee, S.H.[Sang Hwa],
Kanatsugu, Y.[Yasuaki],
Park, J.I.[Jong-Il],
Hierarchical stochastic diffusion for disparity estimation,
SMBV01(xx-yy).
0110
BibRef
Wu, Q.,
Xu, G.,
Ai, H.,
MCGE: Multi-candidate Based Group Evolution in Stereo Matching,
ICIP01(III: 927-930).
IEEE DOI
0108
BibRef
Luo, L.,
Clewer, D.,
Canagarajah, N.,
Bull, D.R.,
Genetic Stereo Matching Using Complex Conjugate Wavelet Pyramids,
ICIP01(II: 153-156).
IEEE DOI
0108
See also Image Fusion Using Complex Wavelets.
BibRef
Hansen, M.,
Daniilidis, K.,
Sommer, G.,
Optimization of stereo disparity estimation using the instantaneous
frequency,
CAIP97(321-328).
Springer DOI
9709
BibRef
Vaidya, N.M., and
Boyer, K.L.,
Stereopsis and Image Registration from Extended Edge Features in
the Absence of Camera Pose Information,
CVPR91(76-82).
IEEE DOI Hypothesize the match using relational constraints.
BibRef
9100
Venkateswar, V., and
Chellappa, R.,
Hierarchical Stereo and Motion Correspondence Using Feature Groupings,
IJCV(15), No. 3, July 1995, pp. 245-269.
Springer DOI
BibRef
9507
Earlier:
Hierarchical Stereo Matching Using Feature Grouping,
DARPA92(427-436).
BibRef
Earlier:
Hierarchical Feature Based Matching for Motion Correspondence,
Motion91(280-285).
Stereo using different features, and extensions to general matching for
motion.
For his thesis:
See also Hierarchical Representation, Matching and Search for Some Computer Vision Problems.
See also Stereo Error Detection, Correction, and Evaluation.
BibRef
Nishimoto, Y., and
Shirai, Y.,
A Parallel Matching Algorithm for Stereo Vision,
IJCAI85(977-980).
Use Zero crossing from several channels (resolutions).
BibRef
8500
Chang, C.C.[Chien-Chung],
Chatterjee, S.,
Kube, P.R.,
A quantization error analysis for convergent stereo,
ICIP94(II: 735-739).
IEEE DOI
9411
BibRef
Earlier:
On an Analysis of Static Occlusion in Stereo Vision,
CVPR91(722-723).
IEEE DOI Match left to right, then right to left and integrate.
BibRef
Chang, C.C.[Chien-Chung],
Chatterjee, S.,
Multiresolution Stereo: A Bayesian Approach,
ICPR90(I: 908-912).
IEEE DOI
BibRef
9000
Chang, C.C.[Chien-Chung],
Chatterjee, S.,
A Deterministic Approach for Stereo Disparity Calculation,
ECCV92(420-424).
Springer DOI
BibRef
9200
Kumar, K.S.,
Desai, U.B.,
Integrated Stereo Vision - A Multiresolution Approach,
ICPR94(A:714-716).
IEEE DOI
BibRef
9400
Ma, R.H.[Rui-Hua],
Thonnat, M.[Monique],
Berthod, M.[Marc],
An Adjustment-Free Stereo Matching Algorithm,
BMVC93(xx-yy).
PDF File.
9309
BibRef
Meygret, A.,
Thonnat, M., and
Berthod, M.,
A Pyramidal Stereovision Algorithm Based on Contour Chain Points,
ECCV90(83-88).
Springer DOI
Pyramid Structure. Reduce time and match main
structure first using pyramid.
BibRef
9000
Yokoya, N.,
Surface Reconstruction Directly From Binocular
Stereo Images By Multiscale-Multistage Regularization,
ICPR92(I:642-646).
IEEE DOI
BibRef
9200
Gu, C.[Chuang],
Wu, L.D.[Le-De],
Structural matching of multiresolution for stereo vision,
ICPR90(I: 243-245).
IEEE DOI
9006
BibRef
Cantoni, V.,
Griffini, A.,
Lombardi, L.,
Stereo Vision In Multi-Resolution,
CIAP89(706-713).
BibRef
8900
Chapter on Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular continues in
Stereo Analysis: Regions, Combine Area and Edge .