10.1.2 Stereo Analysis: Point Matching

Cottafava, G., and LeMoli, G.,
The Automated Contour Map,
CACM(12), No. 7, July 1969, pp. 386-391. BibRef 6907

Mori, K., Kidode, M., and Asada, H.,
An Iterative Prediction and Correction Method for Automatic Stereo Comparison,
CGIP(2), 1973, pp. 393-401. BibRef 7300

Dev, P.,
Perception of Depth Surfaces in Random-Dot Stereograms: A Neural Model,
MMS(7), 1978, pp. 511-528. BibRef 7800

Grimson, W.E.L.,
Computational Experiments with a Feature Based Stereo Algorithm,
PAMI(7), No. 1, January 1985, pp. 17-34. BibRef 8501
And: MIT AI Memo-762, January 1984. Stereo, Grimson. Description of the new Grimson algorithm that uses the modifications suggested by the work since 1980. The major changes are in the area of matching. Very detailed description of the algorithm and the implementation. See also From Images to Surfaces: A Computational Study of the Human Early Visual System. BibRef

Drumheller, M., and Poggio, T.A.,
On Parallel Stereo,
CRA87(527-538). BibRef 8700
And: Same title. CRA86(1439-1448). BibRef

Drumheller, M.,
Connection Machine Stereomatching,
AAAI-86(748-753). BibRef 8600

White, S.,
Stereo Using the Displacement Representation,
DARPA92(391-399). Scale space extraction of disparities. BibRef 9200

Prazdny, K.,
Detection of Binocular Disparities,
BioCyber(52), 1985, pp. 93-99. BibRef 8500
And: RCV87(73-79). Relaxation. Generate all possible disparities, then use a relaxation procedure to get some neighborhood consistency. BibRef

Prazdny, K.,
The Role of Eye Position Information in Algorithms for Stereoscopic Matching,
AAAI-82(1-4). BibRef 8200

Jones, D.G., Malik, J.,
Computational Framework for Determining Stereo Correspondence from a Set of Linear Spatial Filters,
IVC(10), No. 10, December 1992, pp. 699-708.
WWW Version. BibRef 9212
Earlier: ECCV92(395-410).
Springer DOI Link BibRef
And: UCBCSD-91-655, October 1991. BibRef

Gerstenberger, J.S.[Jeffrey S.],
Mechanism for determining parallax between digital images,
US_Patent5,220,441, Jun 15, 1993
WWW Version. Correlation matching. BibRef 9306

Kara, A.[Atsushi], Wilkes, D.M.[D. Mitchell], Kawamura, K.[Kazuhiko],
3D Structure Reconstruction from Point Correspondences between Two Perspective Projections,
CVGIP(60), No. 3, November 1994, pp. 392-397.
WWW Version. BibRef 9411

Reimann, D., Haken, H.,
Stereo Vision by Self-Organization,
BioCyber(71), No. 1, 1994, pp. 17-26. Disparity at each point, relaxation process. BibRef 9400

Agouris, P., Schenk, T.,
Automated Aerotriangulation Using Multiple Image Multipoint Matching,
PhEngRS(62), No. 6, June 1996, pp. 703-710. 9606
BibRef

Toth, C.K., Krupnik, A.,
Concept, Implementation, and Results of an Automatic Aerotriangulation System,
PhEngRS(62), No. 6, June 1996, pp. 711-717. 9606
BibRef

Toth, C.K.[Charles K.], Schenk, T.[Toni],
Multiple image matching in an automatic aerotriangulation system,
CAIP93(750-758).
Springer DOI Link 9309
BibRef

March, R.,
Computation of Stereo Disparity Using Regularization,
PRL(8), 1988, pp. 181-187. BibRef 8800

March, R.,
A Regularization Model for Stereo Vision with Controlled Continuity,
PRL(10), 1989, pp. 259-263. BibRef 8900

Baillard, C., Dissard, O., Jamet, O., Maitre, H.,
Extraction and Textural Characterization of Aboveground Areas from Aerial Stereo Pairs: A Quality Assessment,
PandRS(53), No. 2, April 1998, pp. 130-141. 9805
See also Above-Ground Objects in Urban Scenes from Medium Scale Aerial Imagery. BibRef

Scharstein, D.[Daniel], Szeliski, R.S.[Richard S.],
Stereo Matching With Nonlinear Diffusion,
IJCV(28), No. 2, June-July 1998, pp. 155-174.
WWW Version. 9808
BibRef
Earlier: CVPR96(343-350).
IEEE Abstract. IEEE Top Reference.
WWW Version. BibRef
And: CornellComputer Science, TR96-1575, March 1996. Code, Stereo. Code:
HTML Version. Point matching using Sum of Squared Differences (SSD). BibRef

Scharstein, D.,
Matching Images by Comparing Their Gradient Fields,
ICPR94(A:572-575).
IEEE DOI Link BibRef 9400

Szeliski, R.S.[Richard S.], Scharstein, D.,
Symmetric Sub-Pixel Stereo Matching,
ECCV02(II: 525 ff.).
HTML Version. 0205
BibRef

Chen, T.Y., Bovik, A.C.[Alan C.], Cormack, L.K.[Lawrence K.],
Stereoscopic Ranging by Matching Image Modulations,
IP(8), No. 6, June 1999, pp. 785-797.
IEEE DOI Link BibRef 9906

Birchfield, S.T.[Stan T.], Tomasi, C.[Carlo],
Depth Discontinuities by Pixel-to-Pixel Stereo,
IJCV(35), No. 3, December 1999, pp. 269-293.
WWW Version. BibRef 9912
Earlier: ICCV98(1073-1080).
IEEE DOI Link BibRef
And: STAN-CS--TR-96-1573, Stanford Univ. July 1996. BibRef

Mühlmann, K.[Karsten], Maier, D.[Dennis], Hesser, J.[Jürgen], Männer, R.[Reinhard],
Calculating Dense Disparity Maps from Color Stereo Images, an Efficient Implementation,
IJCV(47), No. 1-3, April-June 2002, pp. 79-88.
WWW Version. 0203
BibRef
Earlier: SMBV01(xx-yy). 0110
BibRef

Wiora, G.[Georg], Babrou, P.[Pavel], Männer, R.[Reinhard],
Real Time High Speed Measurement of Photogrammetric Targets,
DAGM04(562-569).
WWW Version. 0505
BibRef

Okutomi, M.[Masatoshi], Katayama, Y.[Yasuhiro], Oka, S.[Setsuko],
A Simple Stereo Algorithm to Recover Precise Object Boundaries and Smooth Surfaces,
IJCV(47), No. 1-3, April-June 2002, pp. 261-273.
WWW Version. 0203
BibRef
Earlier: CVPR01(II:138-144).
IEEE Abstract. IEEE Top Reference. 0110
BibRef
And: A1, A2 only:
Simple Stereo Algorithm to Recover Precise Object Boundaries and Smooth Surfaces,
SMBV01(xx-yy). 0110
Area based matching. Adaptive. Use multiple pairs and multiple windows to limit area matching errors. BibRef

Lhuillier, M.[Maxime], Quan, L.[Long],
Match Propagation for Image-Based Modeling and Rendering,
PAMI(24), No. 8, August 2002, pp. 1140-1146.
IEEE Abstract. IEEE Top Reference. 0208
Image Based Rendering. Start from sparse set of seed matches, propagate to neighbors. The procedure can generate inbetween images (blended images). BibRef

Lhuillier, M.[Maxime], Quan, L.[Long],
A Quasi-Dense Approach to Surface Reconstruction from Uncalibrated Images,
PAMI(27), No. 3, March 2005, pp. 418-433.
IEEE Abstract. IEEE Top Reference. 0501
BibRef
Earlier:
Quasi-Dense Reconstruction from Image Sequence,
ECCV02(II: 125 ff.).
HTML Version. 0205
BibRef
Earlier:
Robust Dense Matching Using Local and Global Geometric Constraints,
ICPR00(Vol I: 968-972).
IEEE DOI Link
HTML Version. 0009
Structure from resampled dense matches rather than just feature points. BibRef

Zeng, G.[Gang], Paris, S.[Sylvain], Quan, L.[Long], Lhuillier, M.[Maxime],
Surface Reconstruction by Propagating 3D Stereo Data in Multiple 2D Images,
ECCV04(Vol I: 163-174).
WWW Version. 0405
See also Accurate and Scalable Surface Representation and Reconstruction from Images. BibRef

Lhuillier, M.,
Efficient Dense Matching for Textured Scenes using Region Growing,
BMVC98(xx-yy). BibRef 9800

Xiao, J.X.[Jian-Xiong], Chen, J.N.[Jing-Ni], Yeung, D.Y.[Dit-Yan], Quan, L.[Long],
Learning Two-View Stereo Matching,
ECCV08(III: 15-27).
Springer DOI Link 0810
BibRef

Torr, P.H.S., Criminisi, A.,
Dense stereo using pivoted dynamic programming,
IVC(22), No. 10, 1 September 2004, pp. 795-806.
WWW Version. 0409
BibRef
Earlier: BMVC02(3D and Video). 0208
BibRef

Criminisi, A., Blake, A., Rother, C., Shotton, J.D.J., Torr, P.H.S.,
Efficient Dense Stereo with Occlusions for New View-Synthesis by Four-State Dynamic Programming,
IJCV(71), No. 1, January 2007, pp. 89-110.
Springer DOI Link 0609
With view synthesis. 4-state matching to deal with occlusions. Synthesis by direct projection of minimal cost surface. BibRef

Binaghi, E.[Elisabetta], Gallo, I.[Ignazio], Marino, G.[Giuseppe], Raspanti, M.[Mario],
Neural adaptive stereo matching,
PRL(25), No. 15, November 2004, pp. 1743-1758.
WWW Version. 0411
BibRef

Binaghi, E.[Elisabetta], Gallo, I.[Ignazio], Guidali, A., Raspanti, M.[Mario], Salvini, G.,
Adaptive Neural Regularization Assignment for Semi-Blind Biomedical Image Restoration,
IMVIP07(207-207).
IEEE DOI Link 0709
BibRef

Gallo, I.[Ignazio], Binaghi, E.[Elisabetta], Raspanti, M.[Mario],
Neural disparity computation for dense two-frame stereo correspondence,
PRL(29), No. 5, 1 April 2008, pp. 673-687.
WWW Version. 0802
Stereo matching; Occlusion; Disparity space; Neural networks BibRef

Vanetti, M.[Marco], Gallo, I.[Ignazio], Binaghi, E.[Elisabetta],
Dense Two-Frame Stereo Correspondence by Self-organizing Neural Network,
CIAP09(1035-1042).
Springer DOI Link 0909
BibRef

Gallo, I.[Ignazio], Binaghi, E.[Elisabetta],
Dense Stereo Matching with Growing Aggregation and Neural Learning,
VISAPP06(343-353).
Springer DOI Link 0711
BibRef

Miyazawa, K.[Kazuyuki], Aoki, T.[Takafumi],
A robot-based 3D body scanning system using passive stereo vision,
ICIP08(305-308).
IEEE DOI Link 0810
BibRef

Shibahara, T.[Takuma], Aoki, T.[Takafumi], Nakajima, H.[Hiroshi], Kobayashi, K.[Koji],
A Sub-Pixel Stereo Correspondence Technique Based on 1D Phase-only Correlation,
ICIP07(V: 221-224).
IEEE DOI Link 0709
BibRef

Galarza, L., Candocia, F.M.,
Optimal and Dense Small Baseline Stereo Image Correspondence,
ICIP06(1037-1040). 0610

IEEE DOI Link BibRef

Sizintsev, M.[Mikhail],
Hierarchical Stereo with Thin Structures and Transparency,
CRV08(97-104).
IEEE DOI Link 0805
BibRef

Sizintsev, M.[Mikhail], Wildes, R.P.[Richard P.],
Spatiotemporal stereo via spatiotemporal quadric element (stequel) matching,
CVPR09(493-500).
IEEE DOI Link 0906
BibRef
Earlier:
Efficient Stereo with Accurate 3-D Boundaries,
BMVC06(I:237).
PDF Version. 0609
BibRef

Zhou, W.[Wei], Kambhamettu, C.[Chandra],
Binocular Stereo Dense Matching in the Presence of Specular Reflections,
CVPR06(II: 2363-2370).
IEEE DOI Link 0606
BibRef

Schlesinger, D.[Dmitrij], Flach, B.[Boris], Shekhovtsov, A.[Alexander],
A Higher Order MRF-Model for Stereo-Reconstruction,
DAGM04(440-446).
WWW Version. 0505
BibRef

Bovyrin, A., Eruhimov, V., Molinov, S., Mosyagin, V., Pisarevsky, V.,
Fast and robust dense stereo correspondence by column segmentation,
ICIP03(III: 1033-1036).
IEEE Abstract. IEEE Top Reference. 0312
BibRef

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

Jin, K., Boufama, B.,
Towards a Fast and Reliable Dense Matching Algorithm,
VI02(178).
PDF Version. 0208
BibRef

Falkenhagen, L.[Lutz], Wedi, T.[Thomas],
Improving Block-Based Disparity Estimation by Considering the Non-uniform Distribution of the Estimation Error,
SMILE98(xx-yy). BibRef 9800

El Zaart, A., Ziou, D.[Djemel], Dubeau, F.[Francois],
Phase-Based Disparity Estimation: a Spatial Approach,
ICIP97(III: 244-247).
IEEE DOI Link BibRef 9700

Maimone, M.W.[Mark W.], and Shafer, S.A.[Steven A.],
Modeling Foreshortening in Stereo Vision using Local Spatial Frequency,
IROS95(xx). BibRef 9500
And: CMU-CS-TR-95-104, January 1995. Gabor Filter. Phase-Based.
HTML Version. (Html based) and
Postscript Version. (postscript). Plus Errata:
Postscript Version. BibRef

Maimone, M.W.[Mark W.],
Characterizing Stereo Matching Problems using Local Spatial Frequency,
CMU-CS-TR-96-125, May 1996. BibRef 9605 Ph.D.Thesis.
Postscript Version. BibRef

Hannah, M.J.,
Computer Matching of Areas in Stereo Imagery,
Ph.D.Thesis (CS), 1978. BibRef 7800 Stanford AIMemo 239 BibRef
And: Stanford CS Memo STAN-CS-74-438, July 1978. Precursor of Gennery and follower of Quam. Stereo analysis with arbitrary initial camera locations. Computes the camera model by least squares error analysis from a set of matching points. Extends the area of matching points by growing regions which have the same or close disparities. BibRef

Hannah, M.J.,
Bootstrap Stereo,
AAAI-80(38-40). BibRef 8000
And: DARPA80(201-208). BibRef
And:
Bootstrap Stereo Error Simulations,
DARPA81(131-135). A sequence of images is used to generate motion and depth information. The first pair is used to provide an estimate of the camera changes and to give some 3-D information to be used in the sequence. The new areas of the images are analyzed to find new feature points for the next image in the sequence. BibRef

Hannah, M.J.,
SRI's Baseline Stereo System,
DARPA85(149-155). Find matches at different scales using lower levels to guide the higher resolution matches. BibRef 8500

Hannah, M.J.,
Test Results from SRI's Stereo System,
DARPA88(740-744). Results on the photogrammetry data set for the stereo program. BibRef 8800

Hannah, M.J.,
Detection of Errors in Match Disparities,
DARPA82(283-285). BibRef 8200

Gennery, D.B.,
Modelling the Environment of an Exploring Vehicle by Means of Stereo Vision,
Ph.D.June 1980. BibRef 8006 Stanford BibRef

Gennery, D.B.,
Object Detection and Measurement Using Stereo Vision,
DARPA80(161-167). BibRef 8000
And: IJCAI79(320-327). BibRef
Earlier:
A Stereo Vision System for an Autonomous Vehicle,
IJCAI77(576-582). BibRef
And:
A Stereo Vision System,
DARPAO77(31-46). See also Visual Tracking of Known Three-Dimensional Objects. BibRef

Arnold, R.D., and Binford, T.O.,
Geometric Constraints in Stereo Vision,
SPIE(238), San Diego, CA, July 1980, pp. 281-292. BibRef 8007

Arnold, R.D.,
Automated Stereo Perception,
Ph.D.Thesis (cs), 1983. BibRef 8300 Stanford AIMemo 351 BibRef
And: Stanford CS Memo STAN-CS-83-961. BibRef
Earlier:
Local Context in Matching Edges for Stereo Vision,
DARPA78(65-72). BibRef
Earlier:
Spatial Understanding,
DARPA77(1-4). Combines the work of Moravec and Gennery to do a match using corner type features. BibRef

Szeliski, R.S.[Richard S.], and Hinton, G.E.[Geoffrey E.],
Solving Random-Dot Stereograms Using the Heat Equation,
CVPR85(284-288). Simplification of the new work of Prazdny, by implementing as Heat equation. BibRef 8500

Essafi, H., Mazzoni, C., Julien, P.,
Satellite Digital Elevation Model on the Heterogeneous OPENVISION Parallel Computer,
CAMP95(xx). BibRef 9500

Koschan, A.F., Rodehorst, V., Spiller, K.,
Color Stereo Vision Using Hierarchical Block Matching and Active Color Illumination,
ICPR96(I: 835-839).
IEEE DOI Link 9608
(Technical Univ. of Berlin, D) BibRef

Koschan, A.F., Rodehorst, V.,
Towards Real-Time Stereo Employing Parallel Algorithms for Edge-Based and Dense Stereo Matching,
CAMP95(xx). BibRef 9500

Koschan, A.F.[Andreas F.],
Dense stereo correspondence using polychromatic block matching,
CAIP93(538-542).
Springer DOI Link 9309
BibRef

Shah, J.,
A Nonlinear Diffusion Model for Discontinuous Disparity and Half-Occlusions in Stereo,
CVPR93(34-40).
IEEE Abstract. IEEE Top Reference. An approach to stereo correspondence. BibRef 9300

Xie, M.[Ming], Thonnat, M.[Monique],
A theory of 3D reconstruction of heterogeneous edge primitives from two perspective views,
ECCV92(715-719).
Springer DOI Link 9205
BibRef

Bandopadhy, A.,
Interest Points, Disparities and Correspondence,
DARPA84(184-187). (U. of Rochester) BibRef 8400

Shizawa, M.,
Direct Estimation of Multiple Disparities for Transparent Multiple Surfaces in Binocular Stereo,
ICCV93(447-454).
IEEE DOI Link Developed from work in motion section on transparent surfaces. See also On visual ambiguities due to transparency in motion and stereo. BibRef 9300

Gennert, M.A.,
Brightness-Based Stereo Matching,
ICCV88(139-143).
IEEE Abstract. IEEE Top Reference. BibRef 8800

Sato, T.,
Automotive Stereo Vision Using Deconvolution Technique,
IJCAI79(763-765). BibRef 7900

Chapter on Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular continues in
Edge Based Stereo Analysis: Scan Line Oriented .