10.1.6 Line Segment Based Stereo Analysis, Line Matching

Chapter Contents (Back)
Matching, Lines. Stereo, Line Segments.
See also 2-D Line Segments with 2-D Structure.

Perkins, D.,
On Stereo Perception of Line Drawing Pairs,
Ph.D.Thesis, October 1970. BibRef 7010 MITMath. BibRef

Ayache, N.J., and Faverjon, B.,
Efficient Registration of Stereo Images by Matching Graph Descriptions of Edge Segments,
IJCV(1), No. 2, 1987, pp. 107-132.
Springer DOI BibRef 8700
Earlier:
Fast Stereo Matching of Edges Segments Using Prediction and Verification of Hypotheses,
CVPR85(662-664). BibRef
And:
A Fast Stereovision Matcher Based on Prediction and Recursive Verification of Hypothesis,
CVWS85(27-37). Matching, Edges. Edge based stereo, match line segments and propagate to neighbors. The most matches signals the best match. Starts with different initial possible matches. BibRef

Medioni, G.G.[Gerard G.], Nevatia, R.[Ramakant],
Segment-Based Stereo Matching,
CVGIP(31), No. 1, July 1985, pp. 2-18.
Elsevier DOI BibRef 8507 USC Computer Vision
PDF File. BibRef
Earlier: DARPA83(128-136). Matching, Edges. Similar idea to the stereo work of Baker, except that it uses the entire segment in the matching process, not just individual points. use stereo assumptions to limit the search area for matching lines and do the complete search. (
See also Matching Images Using Linear Features. ) BibRef

Grimson, W.E.L.,
Computing Stereopsis Using Feature Point Contour Matching,
T3DMP86(75-111). BibRef 8600

Sherman, D., and Peleg, S.,
Stereo by Incremental Matching of Contours,
PAMI(12), No. 11, November 1990, pp. 1102-1106.
IEEE DOI Match portions of contours in the two images using order constraints. From the set of partial contour matches, interpolate disparities for the entire image and generate iso-depth contour map and other displays. BibRef 9011

Kass, M.,
Linear Image Features in Stereopsis,
IJCV(1), No. 4, January, 1988, pp. 357-368.
Springer DOI BibRef 8801
Earlier: AAAI-86(707-713). Analysis of the effects of changing viewing position on the filter output, and some justification for using edges for stereo. BibRef

Nasrabadi, N.M.[Nasser M.], Liu, Y.[Yi],
Stereo Vision Correspondence Using a Multichannel Graph Matching Technique,
IVC(7), No. 4, November 1989, pp. 237-245.
Elsevier DOI BibRef 8911

Nasrabadi, N.M.[Nasser M.],
A Stereo Vision Technique Using Curve-Segments and Relaxation Matching,
PAMI(14), No. 5, May 1992, pp. 566-572.
IEEE DOI BibRef 9205
Earlier: with: Chiang, J.L., ICPR88(I: 149-151).
IEEE DOI Uses zero-crossings in match. BibRef

Brint, A.T.[Andrew T.], Brady, M.[Michael],
Stereo Matching of Curves,
IVC(8), No. 1, February 1990, pp. 50-56.
Elsevier DOI BibRef 9002

Kim, Y.C., and Aggarwal, J.K.,
Positioning Three-Dimensional Objects Using Stereo Images,
RA(3), No. 4, August, 1987, pp. 361-373. BibRef 8708
Earlier:
Finding Range From Stereo Images,
CVPR85(289-294). (Univ. of Texas) Relaxation. Using zero crossings, find the matching 3X3 patterns and apply a relaxation scheme to get continuity between lines and along the scan line. The 3-D information comes directly, only at matched edges.
See also Rectangular Parallelepiped Coding: A Volumetric Representation of Three-Dimensional Objects. BibRef

Jordan, III, J.R.[John R.], Bovik, A.C.[Alan C.],
Using Chromatic Information in Dense Stereo Correspondence,
PR(25), No. 4, April 1992, pp. 367-383.
Elsevier DOI BibRef 9204

Jordan, III, J.R.[John R.], Bovik, A.C.[Alan C.],
Using Chromatic Information in Edge-Based Stereo Correspondence,
CVGIP(54), No. 1, July 1991, pp. 98-118.
Elsevier DOI BibRef 9107
Earlier:
Computational Stereo Using Color,
SMC-C87(xx) Edges, Color. Include color in addition to the usual intensity. BibRef

Jordan, III, J.R.[John R.], Bovik, A.C.[Alan C.], Geisler, W.S.,
Chromatic Stereopsis,
IJCAI89(1649-1654). BibRef 8900
And:
Chromaticity as a Source of Information in the Human Stereo Correspondence Problem,
SMC-C87(xx). BibRef

Kim, N.H.[Nak H.], Bovik, A.C.[Alan C.],
A Contour-Based Stereo Matching Algorithm Using Disparity Continuity,
PR(21), No. 5, 1988, pp. 505-514.
Elsevier DOI Disparity continutiy along contour. BibRef 8800

Krotkov, E.P., Henriksen, K., and Kories, R.,
Stereo Ranging with Verging Cameras,
PAMI(12), No. 12, December 1990, pp. 1200-1205.
IEEE DOI Active Vision, Vergence. BibRef 9012

Pridmore, T.P.[Tony P.], Mayhew, J.E.W.[John E.W.], Frisby, J.P.[John P.],
Exploiting Image-Plane Data in the Interpretation of Edge-Based Binocular Disparity,
CVGIP(52), No. 1, October 1990, pp. 1-25. Combine linked
Elsevier DOI edges in intensity and in disparity to improve the results in both. BibRef 9010

Boyer, K.L., Wuescher, D.M., Sarkar, S.,
Dynamic Edge Warping: An Experimental System for Recovering Disparity Maps in Weakly Constrained Systems,
SMC(21), 1991, pp. 143-158. BibRef 9100
Earlier:
Dynamic Edge Warping: Experiments in Disparity Estimation under Weak Constraints,
ICCV90(471-475).
IEEE DOI BibRef

Crowley, J.L., Bobet, P., and Sarachik, K.,
Dynamic World Modeling Using Vertical Line Stereo,
RobAS(6), June 1991, pp. xx. BibRef 9106
Earlier: ECCV90(241-246).
Springer DOI Vertical lines only, for indoor scenes. BibRef

Kim, D.H.[Dong H.], Park, R.H.[Rae-Hong],
Analysis Of Quantization-Error in Line-Based Stereo Matching,
PR(27), No. 7, July 1994, pp. 913-924.
Elsevier DOI BibRef 9407

Kanade, T., Okutomi, M.,
A Stereo Matching Algorithm with an Adaptive Window: Theory and Experiment,
PAMI(16), No. 9, September 1994, pp. 920-932.
IEEE DOI BibRef 9409
Earlier: DARPA90(383-398). BibRef
And: CRA91(1088-1095). BibRef
And: CMU-CS-TR-90-120, CMU CS Dept., April 1990. BibRef

Okutomi, M., and Kanade, T.,
A Locally Adaptive window for Signal Matching,
IJCV(7), No. 2, January 1992, pp. 143-162.
Springer DOI BibRef 9201
And: ICCV90(190-199).
IEEE DOI The match window is modified according to the variation of intensity within the window. BibRef

Dhond, U.R., Aggarwal, J.K.,
Stereo Matching in the Presence of Narrow Occluding Objects Using Dynamic Disparity Search,
PAMI(17), No. 7, July 1995, pp. 719-724.
IEEE DOI BibRef 9507
Earlier:
Computing stereo correspondences in the presence of narrow occluding objects,
CVPR92(758-760).
IEEE DOI 0403
BibRef
And:
Analysis of the Stereo Correspondence Process in Scenes with Narrow Occluding Objects,
ICPR92(I:470-473).
IEEE DOI Thin occluding objects violate the ordering constraint usually used. Uses multiple disparity "pools" in matching. BibRef

Dhond, U.R.,
Stereo Matching in the Presence of Narrow Occluding Objects,
Ph.D.ECS, August, 1992. BibRef 9208 Univ. of Texas BibRef

Ruichek, Y., Postaire, J.G.,
A Neural Matching Algorithm for 3-D Reconstruction from Stereo Pairs of Linear Images,
PRL(17), No. 4, April 4 1996, pp. 387-398. 9605

See also New Neural Real-Time Implementation for Obstacle Detection using Linear Stereo Vision, A. BibRef

Bigand, A., Bouwmans, T., Dubus, J.P.,
A new stereomatching algorithm based on linear features and the fuzzy integral,
PRL(22), No. 2, February 2001, pp. 133-146.
Elsevier DOI 0101
BibRef

Prakoonwit, S.[Simant], Benjamin, R.[Ralph],
3D surface point and wireframe reconstruction from multiview photographic images,
IVC(25), No. 9, 1 September 2007, pp. 1509-1518.
Elsevier DOI 0707
3D reconstruction; Apparent contour; Contour generator; Epipolar; Multiview; Space curve; Surface point; Wireframe BibRef

Karimian, G.[Ghader], Raie, A.A.[Abolghasem A.], Faez, K.[Karim],
A New Efficient Stereo Line Segment Matching Algorithm Based on More Effective Usage of the Photometric, Geometric and Structural Information,
IEICE(E89-D), No. 7, July 2006, pp. 2012-2020.
DOI Link 0607
BibRef

Fotouhi, A.M.[Ali M.], Raie, A.A.[Abolghasem A.],
An Efficient Local Stereo Matching Algorithm for Dense Disparity Map Estimation Based on More Effective Use of Intensity Information and Matching Constraints,
IEICE(E92-D), No. 5, May 2009, pp. 1159-1167.
WWW Link. 0907
BibRef

Kim, H.W.[Hyun-Woo], Lee, S.[Sukhan],
Simultaneous line matching and epipolar geometry estimation based on the intersection context of coplanar line pairs,
PRL(33), No. 10, 15 July 2012, pp. 1349-1363.
Elsevier DOI 1205
Line matching; Scene modeling; Line coplanarity; Epipolar geometry estimation BibRef

Mosaddegh, S.[Saleh], Fofi, D.[David], Vasseur, P.[Pascal],
Two View Line-Based Motion and Structure Estimation for Planar Scenes,
ELCVIA(11), No. 1, 2012, pp. xx-yy.
DOI Link 1204
BibRef
Earlier:
Line based motion estimation and reconstruction of piece-wise planar scenes,
WMVC11(658-663).
IEEE DOI 1101

See also Short baseline line matching for central imaging systems. 2 views, minimum line correspondences. BibRef
Earlier:
Motion estimation and reconstruction of piecewise planar scenes from two views,
IVCNZ10(1-7).
IEEE DOI 1203
BibRef

Ok, A.O.[Ali Ozgun], Wegner, J.D.[Jan Dirk], Heipke, C.[Christian], Rottensteiner, F.[Franz], Soergel, U.[Uwe], Toprak, V.[Vedat],
Matching of straight line segments from aerial stereo images of urban areas,
PandRS(74), No. 1, November 2012, pp. 133-152.
Elsevier DOI 1212
Image matching; Line segment matching; Stereo images; Aerial imagery; Urban areas BibRef

Cigla, C.[Cevahir], Alatan, A.A.[A. Aydin],
Information permeability for stereo matching,
SP:IC(28), No. 9, 2013, pp. 1072-1088.
Elsevier DOI 1310
BibRef
Earlier:
Efficient edge-preserving stereo matching,
Dense11(696-699).
IEEE DOI 1201
Dense disparity map BibRef

Cigla, C.[Cevahir], Zabulis, X.[Xenophon], Alatan, A.A.[A. Aydin],
Segment-Based Stereo-Matching Via Plane and Angle Sweeping,
3DTV07(1-4).
IEEE DOI 0705
BibRef

Cheng, F.Y.[Fei-Yang], Zhang, H.[Hong], Sun, M.[Mingui], Yuan, D.[Ding],
Cross-trees, edge and superpixel priors-based cost aggregation for stereo matching,
PR(48), No. 7, 2015, pp. 2269-2278.
Elsevier DOI 1504
Stereo matching BibRef

Li, Y.J.[Ying-Jiang], Zhang, J.W.[Jian-Wei], Zhong, Y.Z.[Yu-Zhong], Wang, M.N.[Mao-Ning],
An efficient stereo matching based on fragment matching,
VC(35), No. 2, February 2019, pp. 257-269.
WWW Link. 1906
BibRef

Li, Y.J.[Ying-Jiang], Zhang, J.W.[Jian-Wei], Zhong, Y.Z.[Yu-Zhong], Wang, M.N.[Mao-Ning],
A fast temporal constraint semi-dense stereo matching method,
SIViP(13), No. 6, September 2019, pp. 1097-1104.
Springer DOI 1908
BibRef

Yue, Y.[Yi], Fang, T.[Tong], Li, W.[Wen], Chen, M.[Min], Xu, B.[Bo], Ge, X.M.[Xu-Ming], Hu, H.[Han], Zhang, Z.[Zhanhao],
Hierarchical Edge-Preserving Dense Matching by Exploiting Reliably Matched Line Segments,
RS(15), No. 17, 2023, pp. 4311.
DOI Link 2310
BibRef


Santos, R.[Roi], Fdez-Vidal, X.R.[Xosé R.], Pardo, X.M.[Xosé M.],
Adaptive Line Matching for Low-Textured Images,
IbPRIA15(192-199).
Springer DOI 1506
BibRef

López, J.[Juan], Fuciños, M.[María], Fdez-Vidal, X.R.[Xosé R.], Pardo, X.M.[Xosé M.],
Detection and Matching of Lines for Close-Range Photogrammetry,
IbPRIA13(732-739).
Springer DOI 1307
BibRef

Song, L.M.[Li-Mei], Wang, L.[Long],
A Thin Line Power Increase Stereo Matching Method Used in High-Precision Three-Dimensional Measurement,
CISP09(1-4).
IEEE DOI 0910
BibRef

Cai, L.L.[Li-Li], Zhang, M.[Ming],
Local Stereo Matching with Edge-Based Cost Aggregation and Occlusion Handling,
CISP09(1-4).
IEEE DOI 0910
BibRef

Pagel, F.[Frank],
A Segment and Fusion-Based Stereo Approach,
CRV09(170-177).
IEEE DOI 0905
BibRef

Wang, W.[Wei], Wang, Y.Z.[Yi-Zhou], Huo, L.S.[Long-She], Huang, Q.M.[Qing-Ming], Gao, W.[Wen],
Symmetric segment-based stereo matching of motion blurred images with illumination variations,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Fu, Z.L.[Zhong-Liang], Sun, Z.Q.[Zhi-Qun],
An Algorithm of Straight Line Features Matching on Aerial Imagery,
ISPRS08(B3b: 97 ff).
PDF File. 0807
BibRef

Klaus, A.[Andreas], Sormann, M.[Mario], Karner, K.[Konrad],
Segment-Based Stereo Matching Using Belief Propagation and a Self-Adapting Dissimilarity Measure,
ICPR06(III: 15-18).
IEEE DOI 0609
BibRef

Evans, M.[Murray], Ferryman, J.M.[James M.],
Global-to-Local Histogram Match Culling for Epipolar Geometry Estimation,
AVSBS06(94-94).
IEEE DOI 0611
BibRef

Evans, M.[Murray], Ferryman, J.M.[James M.],
Cross Validation and Segment Support for Stereo Belief Propagati,
ICPR06(I: 115-118).
IEEE DOI 0609
BibRef

Wang, K.[Kun],
Adaptive stereo matching algorithm based on edge detection,
ICIP04(II: 1345-1348).
IEEE DOI 0505
BibRef

Hong, L.[Li], Chen, G.,
Segment-based stereo matching using graph cuts,
CVPR04(I: 74-81).
IEEE DOI 0408
BibRef

Jung, F.[Franck], Tollu, V.[Vincent], Paparoditis, N.[Nicolas],
Extracting 3D Edgels Hypotheses From Multiple Calibrated Images: A Step Towards Curved Objects Boundary Lines Reconstruction,
PCV02(B: 100). 0305
BibRef

Alibhai, S., Zucker, S.W.,
Contour-based Correspondence for Stereo,
ECCV00(I: 314-330).
Springer DOI 0003
BibRef

Zhang, Z.Y.[Zheng-You], Shan, Y.[Ying],
System and method for progressive stereo matching of digital images,
US_Patent7,106,899, Sep 12, 2006
WWW Link. BibRef 0609
And: US_Patent7,164,790, Jan 16, 2007
WWW Link. BibRef
And: US_Patent7,272,256, Sep 18, 2007
WWW Link. BibRef

Shan, Y.[Ying], Zhang, Z.Y.[Zheng-You],
Corner Guided Curve Matching and its Application to Scene Reconstruction,
CVPR00(I: 796-803).
IEEE DOI 0005
contours contrained by corners! BibRef

Kawai, Y., Tomita, F.,
Intensity Calibration for Stereo Images Based on Segment Correspondence,
MVA98(xx-yy). BibRef 9800

Kawai, Y.[Yoshihiro], Ueshiba, T.[Toshio], Ishiyama, Y.[Yutaka], Sumi, Y.S.[Yasu-Shi], Tomita, F.[Fumiaki],
Stereo correspondence using segment connectivity,
ICPR98(Vol I: 648-651).
IEEE DOI 9808
Title was: A New Method of Segment-Based Stereo Using Connectivity of Segments BibRef

Schreer, O.[Oliver], Hartmann, I.[Irmfried], Adams, R.[Roger],
Analysis of grey-level features for line segment stereo matching,
CIAP97(I: 620-627).
Springer DOI 9709
BibRef

Srinivasan, R., Ramakrishnan, K.R., Sastry, P.S.,
A Contour Based Stereo Algorithm,
ICCV87(677-681). BibRef 8700

Luo, A., Tao, W., Burkhardt, H.,
A New Multilevel Line-Based Stereo Vision Algorithm Based on Fuzzy Techniques,
ICPR96(I: 383-387).
IEEE DOI 9608
(Mikroelektronik Anwendungszentrum GmbH, D) BibRef

Ayache, N.J., Faugeras, O.D.[Olivier D.], Faverjon, B., and Toscani, G.,
Matching Depth Maps Obtained by Passive Stereo,
CVWS85(197-204). The use of the stereo results from Ayache and Faverjon's papers. Seems to be straightforward, choose a possible match and find how many fit, search for the best. Similar to their stereo matching algorithm. BibRef 8500

Faugeras, O.D.[Olivier D.], Ayache, N.J., Faverjon, B., and Lustman, F.,
Building Visual Maps by Combining Noisy Stereo Measurements,
CRA86(1433-1438). Or is it 87?. BibRef 8600

Faugeras, O.D.[Olivier D.], Lustman, F.,
Identifying Planes for the Construction of the World Model of a Mobile Robot,
ICPR86(162-164). BibRef 8600

Li, Z.N., Zhang, D.,
Real-Time Line-Based Motion Stereo,
CRA93(367-372). Parallel hierarchical pyramidal algorithm ; line-based motion stereo. BibRef 9300

Ens, J., and Li, Z.N.,
Real-Time Motion Stereo,
CVPR93(130-135).
IEEE DOI A real-time implementation of multi-baseline stereo with transputer at each of the lowest levels. BibRef 9300

Ji, C.X., Zhang, Z.P.,
Stereo Match Based on Linear Feature,
ICPR88(II: 875-878).
IEEE DOI BibRef 8800

Long Limozin, P., Giraudon, G.,
Stereo Matching Using Contextual Line Region Primitives,
ICPR86(974-977). BibRef 8600

Burr, D.J., and Chien, R.T.,
A System for Stereo Computer Vision with Geometric Models,
IJCAI77(583). BibRef 7700
And: A1 only: Ph.D.Univ. Illinois, 1977 BibRef

Chapter on Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular continues in
Stereo Systems: Multiple Resolutions, Hierarchical .


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