10.1.9 Stereo and Surface Models

Chapter Contents (Back)
Stereo, Surface Models. Surface Reconstruction.

Grimson, W.E.L.,
From Images to Surfaces: A Computational Study of the Human Early Visual System,
Cambridge: MIT Press1981. BibRef 8100 Ph.D.Thesis (EE). BibRef Book BibRef
Aspects of a Computational Theory of Human Stereo Vision,
DARPA80(128-149). Stereo system based on Marr-Poggio (
See also Cooperative Computation of Stereo Disparity. ) theory. See the review in SIGART #82. This is his thesis work turned into a book. For surface interpolation work:
See also Computational Theory of Visual Surface Interpolation, A. BibRef

Ganapathy, S.,
Reconstruction of Scenes Containing Polyhedra from Stereo Pairs of Views,
Stanford AIMemo 272, December 1975. A different date in another reference: BibRef 7512 Ph.D.Thesis (CS), Stanford, 1976. Early Stanford stereo work. BibRef

Boult, T.E., and Chen, L.H.,
Synergistic Smooth Surface Stereo,
IEEE DOI BibRef 8800
And: A2, A1:
An Integrated Approach to Stereo Matching, Surface Reconstruction and Depth Segmentation Using Consistent Smoothness Assumptions,
DARPA88(166-176). BibRef
And: A1, A2:
Analysis of Two New Stereo Algorithms,
IEEE DOI Combine feature matching, surface reconstruction and segmentation of surfaces to get better results. Results in high density disparities. Use current surface information to decide on ambiguous matches. BibRef

Abbott, A.L., and Ahuja, N.,
Active Stereo: Integrating Disparity, Vergence, Focus, Aperture, and Calibration for Surface Estimation,
PAMI(15), No. 10, October 1993, pp. 1007-1029.
IEEE Abstract.
IEEE DOI BibRef 9310
Active Surface Reconstruction by Integrating Focus, Vergence, Stereo, and Camera Calibration,
Surface Reconstruction by Dynamic Integration of Focus, Camera Vergence, and Stereo,
IEEE DOI Active Vision, Vergence. Data Fusion. Combine all information available to the system to get better results. Interleave image acquisition with surface estimation. Obtains very accurate estimates of surface shapes. BibRef

Abbott, A.L.[A. Lynn],
Dynamic Integration of Depth Cues for Surface Reconstruction from Stereo Images,
Ph.D.Thesis (ECE), May 1990, BibRef 9005 Univ. of Illinois(Or is is January 1991). Computational method for surface reconstruction from stereo images using stereo, camera vergence, and focus. BibRef

Olsen, S.I.,
Stereo Correspondence by Surface Reconstruction,
PAMI(12), No. 3, March 1990, pp. 309-315.
IEEE Abstract.
IEEE DOI BibRef 9003
Concurrent Solution of the Stereo Correspondence Problem and the Surface Reconstruction Problem,
ICPR86(1038-1040). Surface Reconstruction. Refine disparities according to the reconstruction from computed disparities. BibRef

Olsen, S.I.,
Epipolar Line Estimation,
Springer DOI BibRef 9200

Chu, C.C.[Chen-Chau], Bovik, A.C.[Alan C.],
Visible Surface Reconstruction Via Local Minimax Approximation,
PR(21), No. 4, 1988, pp. 303-312.
Elsevier DOI Smooth surfaces, but maintain discontinuities. BibRef 8800

O'Neill, M.A.[Mark A.], Denos, M.I.[Mia I.],
Practical Approach to the Stereo Matching of Urban Imagery,
IVC(10), No. 2, March 1992, pp. 89-98.
Elsevier DOI BibRef 9203

O'Neill, M.A.[Mark A.], Denos, M.I.[Mia I.],
Automated-System for Coarse-to-Fine Pyramidal Area Correlation Stereo Matching,
IVC(14), No. 3, April 1996, pp. 225-236.
Elsevier DOI 9607

Denos, M.I.[Mia I.],
An Automated Approach to Stereo Matching Seasat Imagery,
PDF File. 9109

Huang, J.S., Liu, H.C.,
Stereo Vision Using a Microcanonical Mean-Field Annealing Neural-Network,
NetCompNeur(8), No. 1, February 1997, pp. 87-104. 9703

Liu, H.C., Huang, J.S.,
Pattern Recognition Using Evolution Algorithms with Fast Simulated Annealing,
PRL(19), No. 5-6, April 1998, pp. 403-413. 9808

Kanade, T.[Takeo], Narayanan, P.J., Rander, P.W.[Peter W.],
Method for creating virtual reality,
US_Patent6,084,979, Jul 4, 2000
WWW Link. BibRef 0007

Kanade, T., Rander, P.W., Narayanan, P.J.,
Virtualized Reality: Constructing Virtual Worlds From Real Scenes,
MultMed(4), No. 1, Jan-Mar 1997, pp. 34-47. 9704
Image Based Rendering. Graphics. BibRef

Kanade, T.[Takeo], Narayanan, P.J., Rander, P.W.[Peter W.],
Virtualized Reality: Being Mobile in a Visual Scene,
ORCV96(273) 9611
Earlier: A1 only: RVS95(xx). BibRef

Kanade, T.[Takeo], Narayanan, P.J., Rander, P.W.[Peter W.],
Virtualized Reality: Concept and Early Results,
CMU-CS-TR-95-153, August 1995.
PS File. BibRef 9508

Kanade, T.[Takeo], Narayanan, P.J.,
Historical Perspectives on 4D Virtualized Reality,

Narayanan, P.J., Kanade, T.,
Virtual Worlds Using Computer Vision,
CVVRHC98(Sensing and Rendering Real Scenes). BibRef 9800

Narayanan, P.J., Rander, P.W.[Peter W.], and Kanade, T.[Takeo],
Constructing Virtual Worlds Using Dense Stereo,
IEEE DOI BibRef 9800

Rander, P.W.,
A Multi-Camera Method for 3D Digitization of Dynamic, Real-World Events,
CMU-RI-TR-98-12, May, 1998.
HTML Version. BibRef 9805

Szeliski, R.S.[Richard S.], Golland, P.[Polina],
Stereo Matching with Transparency and Matting,
IJCV(32), No. 1, August 1999, pp. 45-61.
DOI Link BibRef 9908
Earlier: ICCV98(517-524).
IEEE DOI Award, Marr Prize, HM. BibRef
And: MicrosoftMSR-TR-97-13, May 1997
PS File. BibRef

Szeliski, R.S.[Richard Stephen], Golland, P.[Polina],
Method for performing stereo matching to recover depths, colors and opacities of surface elements,
US_Patent5,917,937, Jun 29, 1999
WWW Link. BibRef 9906

Zitnick, C.L.[C. Lawrence], Kanade, T.[Takeo],
A Cooperative Algorithm for Stereo Matching and Occlusion Detection,
PAMI(22), No. 7, July 2000, pp. 675-684.
IEEE Abstract.
And: CMU-RI-TR-99-35, October, 1999.
HTML Version. BibRef

Zitnick, C.L., and Kanade, T.,
A Volumetric Iterative Approach to Stereo Matching and Occlusion Detection,
CMU-RI-TR-98-30, December, 1998.
HTML Version. BibRef 9812

Teng, C.H.[Chin-Hung],
Improving three-dimensional point reconstruction from image correspondences using surface curvatures,
MVA(25), No. 2, February 2014, pp. 421-436.
WWW Link. 1402

Mu, T.J.[Tai-Jiang], Sun, J.J.[Jia-Jia], Martin, R.R.[Ralph R.], Hu, S.M.[Shi-Min],
A response time model for abrupt changes in binocular disparity,
VC(31), No. 5, May 2015, pp. 675-687.
WWW Link. 1505

Chang, Y.J.[Yong-Jun], Ho, Y.S.[Yo-Sung],
Disparity map enhancement in pixel based stereo matching method using distance transform,
JVCIR(40, Part A), No. 1, 2016, pp. 118-127.
Elsevier DOI 1609
Stereo matching BibRef

Lee, E.K.[Eun-Kyung], Kim, S.Y.[Sung-Yeol], Jung, Y.K.[Young-Ki], Ho, Y.S.[Yo-Sung],
High-Resolution Depth Map Generation by Applying Stereo Matching Based on Initial Depth Informaton,

Reeves, A.[Adam], Lynch, D.[David],
Transparency in stereopsis: parallel encoding of overlapping depth planes,
JOSA-A(34), No. 8, August 2017, pp. 1424-1432.
DOI Link 1708
Vision-binocular and stereopsis , Psychophysics BibRef

Yoon, S.[Seongwook], Choi, T.[Taehyeon], Sull, S.H.[Sang-Hoon],
Depth estimation from stereo cameras through a curved transparent medium,
PRL(129), 2020, pp. 101-107.
Elsevier DOI 2001
Depth from stereo, Camera calibration, Refraction, Parametric surface model BibRef

Li, Z.H.[Zhi-Hui], Liu, J.X.[Jia-Xin], Yang, Y.[Yang], Zhang, J.[Jing],
A Disparity Refinement Algorithm for Satellite Remote Sensing Images Based on Mean-Shift Plane Segmentation,
RS(13), No. 10, 2021, pp. xx-yy.
DOI Link 2105

Kn÷belreiter, P.[Patrick], Pock, T.[Thomas],
Learned Collaborative Stereo Refinement,
IJCV(129), No. 9, September 2021, pp. 2565-2582.
Springer DOI 2108
Earlier: GCPR19(3-17).
Springer DOI 1911
Award, GCPR. BibRef

Wang, X.Q.[Xuan-Qi], Jiang, L.T.[Li-Ting], Wang, F.[Feng], You, H.J.[Hong-Jian], Xiang, Y.M.[Yu-Ming],
Disparity Refinement for Stereo Matching of High-Resolution Remote Sensing Images Based on GIS Data,
RS(16), No. 3, 2024, pp. 487.
DOI Link 2402

Zhang, C.[Chi], Li, Z.W.[Zhi-Wei], Cai, R.[Rui], Chao, H.Y.[Hong-Yang], Rui, Y.[Yong],
As-Rigid-As-Possible Stereo under Second Order Smoothness Priors,
ECCV14(II: 112-126).
Springer DOI 1408

Yakar, M., Yilmaz, H.M.,
Using in Volume Computing of Digital Close Range Photogrammetry,
ISPRS08(B3b: 119 ff).
PDF File. 0807

Yilmaz, H.M.[H. Murat], Yakar, M.[Murat], Yildiz, F.[Ferruh],
Digital Photogrammetry in Obtaining of 3D Model Data of Irregular Small Surfaces,
ISPRS08(B3b: 125 ff).
PDF File. 0807

Sun, Y.[Yunda], Kohli, P.[Pushmeet], Bray, M.[Matthieu], Torr, P.H.S.[Philip H. S.],
Using Strong Shape Priors for Stereo,
Springer DOI 0612

Louchet, J.[Jean],
Stereo Analysis Using Individual Evolution Strategy,
ICPR00(Vol I: 908-911).
Combine stereo with surfaces to get better stereo. BibRef

Ishikawa, H.[Hiroshi],
Multi-scale Feature Selection in Stereo,
CVPR99(I: 132-137).
IEEE Abstract.
IEEE DOI Use constraints from the surface to limit feature matches. BibRef 9900

Hattori, H.[Hiroshi], Maki, A.[Atsuto],
Stereo without Depth Search and Metric Calibration,
CVPR00(I: 177-184).
IEEE Abstract.
Stereo Matching with Direct Surface Orientation Recovery,
BMVC98(xx-yy). Stereo BibRef

Wang, C., Abe, K.,
Stereo Matching by Integrating Piecewise Surfaces Matched in Subranges of Depth,
ICPR96(I: 423-427).
(Shizuoka Univ., J) BibRef

Ouali, M.H.[Mohammed H.], Ziou, D., Laurgeau, C.,
A Cooperative Multiscale Phase-Based Disparity Algorithm,
IEEE DOI BibRef 9900
Dense disparity estimation using Gabor filters and image derivatives,

Ouali, M.H.[Mohammed H.], Lange, H., Laurgeau, C.,
An Energy Minimization Approach to Dense Stereovision,
ICIP96(II: 841-845).
IEEE DOI BibRef 9600

Dillon, C., Caelli, T.M.,
Generating Complete Depth Maps In Passive Vision Systems,
IEEE DOI BibRef 9200

Butler, N.,
Matching Stereo Satellite Images,
IEEE DOI BibRef 9200

Chapter on Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular continues in
Matching Issues for Stereo .

Last update:May 29, 2024 at 17:34:46