Young, G.S., and
Chellappa, R.,
3-D Motion Estimation Using a Sequence of Noisy Stereo Images:
Models, Estimation, and Uniqueness Results,
PAMI(12), No. 8, August 1990, pp. 735-759.
IEEE DOI
BibRef
9008
Earlier:
CVPR88(710-716).
IEEE DOI Closed form solutions using quaternions.
BibRef
Young, G.S., and
Chellappa, R.,
Statistical Analysis of Inherent Ambiguities in Recovering
3-D Motion from a Noisy Flow Field,
PAMI(14), No. 10, October 1992, pp. 995-1013.
IEEE DOI
BibRef
9210
Earlier:
ICPR90(I: 371-377).
IEEE DOI
BibRef
Chen, H.H.,
Determining Motion and Depth from Binocular Orthographic Views,
CVGIP(54), No. 1, July 1991, pp. 47-55.
Elsevier DOI
BibRef
9107
Earlier:
Motion And Depth From Binocular Orthographic Views,
ICCV88(634-640).
IEEE DOI The Z value from the stereo estimate is discarded thus giving an
Orthographic projection (X and Y only).
See also Using Motion from Orthographic Views to Verify 3-D Point Matches.
BibRef
Abdel-Mottaleb, M.,
Chellappa, R., and
Rosenfeld, A.,
Binocular Motion Stereo Using MAP Estimation,
CVPR93(321-327).
IEEE DOI From the FOE to displacement to a depth map for axial motion.
BibRef
9300
Huang, T.S., and
Blostein, S.D.,
Robust Algorithms for Motion Estimation Based on
Two Sequential Stereo Image Pairs,
CVPR85(518-523). (Univ. of Illinois)
Motion, Estimation Evaluation. Motion with stereo using simulated data. Error analysis for the
expected range of values, 9 points in the views are needed for good
results. With more authors and a new title, essentially the same
thing is in
BibRef
8500
Motion86(45-46).
BibRef
Blostein, S.D., and
Huang, T.S.,
Estimating 3-D Motion from Range Data,
CAIA84(246-250).
BibRef
8400
Hong, Z., and
Ahuja, N.,
Target Tracking and Cumulative
Depth Map Generation from Binocular Image Sequences,
IAS93(xx-yy).
BibRef
9300
Mitiche, A.[Amar], and
Bouthemy, P.[Patrick],
Tracking Modelled Objects Using Binocular Images,
CVGIP(32), No. 3, December 1985, pp. 384-396.
Elsevier DOI
BibRef
8512
And:
Representation and Tracking of Point Structures Using Stereovision,
CVWS84(118-124).
Motion, Structure. From INRS-Telecommunications, 3 place du Commerce,
Ile-des-Soeurs, PQ H3E 1H6. Develops a lot of equations to derive
the motion from a given match which comes from stereo pairs. They
assume that the stereo match can be done in a "brute force" manner
- try all possible and choose the best. The camera parameters then
give 3-D positions that are used in the motion match, which are
then used to derive the motion parameters.
BibRef
Meyer, F.G.,
Bouthemy, P.,
Region-Based Tracking Using Affine Motion Models in
Long Image Sequences,
CVGIP(60), No. 2, September 1994, pp. 119-140.
DOI Link
BibRef
9409
Earlier:
Region-Based Tracking in an Image Sequence,
ECCV92(476-484).
Springer DOI
BibRef
Deriche, R.,
Faugeras, O.D.,
Tracking Line Segments,
IVC(8), No. 4, November 1990, pp. 261-270.
BibRef
9011
Earlier:
ECCV90(259-268).
Springer DOI
BibRef
Zhang, Z.Y., and
Faugeras, O.D.,
Tracking and Grouping 3D Line Segments,
ICCV90(577-580).
IEEE DOI
BibRef
9000
Bascle, B.,
Bouthemy, P.,
Deriche, R.,
Meyer, F.,
Tracking Complex Primitives in an Image Sequence,
ICPR94(A:426-431).
IEEE DOI
BibRef
9400
Giai-Checa, B.,
Bouthemy, P.,
Vieville, T.,
Segment-Based Detection of Moving Objects in a Sequence of Images,
ICPR94(A:384-389).
IEEE DOI
IEEE DOI
BibRef
9400
Mutch, K.M.,
Determining Object Translation Information Using Stereoscopic Motion,
PAMI(8), No. 6, November 1986, pp. 750-755.
BibRef
8611
And:
With:
Heiny, L.C.,
Calculating Object Size from Stereoscopic Motion,
CVPR86(183-187).
Matching is eliminated by using a spot on white background. Assume
the measured dimension is parallel to the camera baseline, and
there is translation.
BibRef
Aggarwal, J.K., and
Magee, M.J.,
Determining Motion Parameters Using Intensity Guided Range Sensing,
PR(19), No. 2, 1986, pp. 169-180.
Elsevier DOI
BibRef
8600
Earlier:
ICPR84(538-541).
Library models are matched to get the rotation and translation
parameters of the object centers which provide the motion
parameters. The other aspect is the intensity and range data
combination work.
See also Experiments in Intensity Guided Range Sensing Recognition of Three-Dimensional Objects.
BibRef
Kim, Y.C., and
Aggarwal, J.K.,
Determining Object Motion in a Sequence of Stereo Images,
RA(3), No. 5, December 1987, pp. 599-614.
See also Positioning Three-Dimensional Objects Using Stereo Images.
BibRef
8712
Zhang, Z.Y., and
Faugeras, O.D.,
3D Dynamic Scene Analysis: A Stereo Based Approach,
SpringerBerlin, Heidelberg, 1992.
BibRef
9200
BookSeveral proposed methods, both long and short sequences. Stereo
results are superior to monocular.
BibRef
Zhang, Z.Y., and
Faugeras, O.D.,
Three-Dimensional Motion Computation and Object Segmentation
in a Long Sequence of Stereo Frames,
IJCV(7), No. 3, April 1992, pp. 211-241.
Springer DOI Track 3-D components and estimate their motion using an extended
Kalman filter. Then group tokens into
objects based on similar motions.
See also Motion of an Uncalibrated Stereo Rig: Self-Calibration and Metric Reconstruction.
BibRef
9204
Zhang, Z.Y.,
Faugeras, O.D., and
Ayache, N.J.,
Analysis of a Sequence of Stereo Scenes Containing Multiple
Moving Objects Using Rigidity Constraints,
ICCV88(177-186).
IEEE DOI Use the trinocular stereo system to generate depth images, match
these and mark as moving anything that is not consistent.
See also Trinocular Stereo Vision for Robotics.
BibRef
8800
Zhang, Z.Y., and
Faugeras, O.D.,
Estimation of Displacements from Two 3-D Frames Obtained from Stereo,
PAMI(14), No. 12, December 1992, pp. 1141-1156.
IEEE DOI
Motion, Lines. Estimate displacement from two stereo frames using lines. It misses
some important multi-frame motion and structure papers. There is a
long bibliography even with these missing papers.
BibRef
9212
Zhang, Z.Y., and
Faugeras, O.D.,
Determining Motion from 3D Line Segment Matches: A Comparative Study,
IVC(9), No. 1, February 1991, pp. 10-19.
Elsevier DOI
BibRef
9102
Earlier:
BMVC90(xx-yy).
PDF File.
9009
SVD. Since the 3D data is extracted, it is noisy. Compares EKF, general
minimization, and SVD.
BibRef
Zhang, Z.Y.[Zheng-You],
Faugeras, O.D.[Olivier D.],
Finding Planes and Clusters of Objects from 3D Line
Segments with Application to 3D Motion Determination,
CVGIP(60), No. 3, November 1994, pp. 267-284.
DOI Link
BibRef
9411
Earlier:
Finding clusters and planes from 3D line segments with application to
3D motion determination,
ECCV92(227-236).
Springer DOI
9205
Find planes based on clusters of line segments
BibRef
Zhang, Z.Y.[Zheng-You],
Motion and Structure of Four Points from One Motion of
a Stereo Rig with Unknown Extrinsic Parameters,
PAMI(17), No. 12, December 1995, pp. 1222-1227.
IEEE DOI
BibRef
9512
And:
Motion of a Stereo Rig: Strong, Weak, and Self-Calibration,
ACCV95(1274-1281).
BibRef
Earlier:
CVPR93(556-561).
IEEE DOI Two stereo pairs, four points, determine camera motion, camera
positions, and structure.
See also Motion of an Uncalibrated Stereo Rig: Self-Calibration and Metric Reconstruction.
BibRef
Zhang, Z.Y.[Zheng-You],
An automatic and robust algorithm for determining motion and structure
from two perspective images,
CAIP95(174-181).
Springer DOI
9509
BibRef
Faugeras, O.D.,
Ayache, N.,
Zhang, Z.Y.,
A Preliminary Investigation of the Problem of Determining
Ego- and Object Motions from Stereo,
ICPR88(I: 242-246).
IEEE DOI
BibRef
8800
Tsukiyama, T.[Toshifumi],
Huang, T.S.[Thomas S.],
Motion Stereo for Navigation of Autonomous Vehicles in
Man-Made Environments,
PR(20), No. 1, 1987, pp. 105-113.
Elsevier DOI
BibRef
8700
Earlier:
ICPR86(165-168).
BibRef
Earlier:
Motion Stereo for Navigation of Autonomous Vehicles in a Passageway,
CVWS85(148-155).
BibRef
Tsukiyama, T.,
Shirai, Y.,
Detection of the Movements of Men for Autonomous Vehicles,
IJCAI79(908-910).
BibRef
7900
Shieh, J.Y.,
Zhuang, H.,
Sudhakar, R.,
Motion Estimation From A Sequence Of Stereo Images: A Direct Method,
SMC(24), No. 7, July 1994, pp. 1044-1053.
BibRef
9407
Liao, W.H.[Wen-Hung],
Aggarwal, S.J.,
Aggarwal, J.K.,
The Reconstruction of Dynamic 3D Structure of Biological Objects
Using Stereo Microscope Images,
MVA(9), No. 4, 1997, pp. 166-178.
Springer DOI
BibRef
9700
Earlier:
Reconstruction of dynamic 3-D structures of biological objects using
stereo microscopy,
ICIP94(III: 731-735).
IEEE DOI
9411
Nonrigid Motion. Image registration by correlation, region of interest using motion based
segmentation, stereo and motion
BibRef
Shih, S.W.,
Hung, Y.P.,
Lin, W.S.,
New Closed-Form Solution for Kinematic Parameter-Identification
of a Binocular Head Using Point Measurements,
SMC-B(28), No. 2, April 1998, pp. 258-267.
IEEE Top Reference.
9804
BibRef
Liao, W.H.,
Aggarwal, J.K.,
Cooperative Matching Paradigm for the Analysis of
Stereo Image Sequences,
IJIST(9), No. 4, 1998, pp. 192-200.
9808
BibRef
Ho, P.K.[Pui-Kuen],
Chung, R.[Ronald],
Stereo-Motion with Stereo and Motion in Complement,
PAMI(22), No. 2, February 2000, pp. 215-220.
IEEE DOI
0003
BibRef
Earlier:
Stereo-Motion That Complements Stereo and Motion Analyses,
CVPR97(213-218).
IEEE DOI
9704
Decompose 3D, into motions, stereogeometry.
BibRef
Dornaika, F.[Fadi],
Chung, C.R.,
Stereo geometry from 3D ego-motion streams,
SMC-B(33), No. 2, April 2003, pp. 308-323.
IEEE Abstract.
0308
BibRef
Dornaika, F.[Fadi],
Chung, R.[Ronald],
Cooperative Stereo-Motion: Matching and Reconstruction,
CVIU(79), No. 3, September 2000, pp. 408-427.
DOI Link
0008
BibRef
Earlier:
Stereo Correspondence from Motion Correspondence,
CVPR99(I: 70-75).
IEEE DOI
BibRef
Ku, J.S.[Ja Seong],
Lee, K.M.[Kyoung Mu],
Lee, S.U.[Sang Uk],
Multi-image matching for a general motion stereo camera model,
PR(34), No. 9, September 2001, pp. 1701-1712.
Elsevier DOI
0108
BibRef
Earlier:
ICIP98(II: 608-612).
IEEE DOI
9810
BibRef
Heo, Y.S.[Yong Seok],
Lee, K.M.[Kyoung Mu],
Lee, S.U.[Sang Uk],
Illumination and camera invariant stereo matching,
CVPR08(1-8).
IEEE DOI
0806
BibRef
Qian, G.[Gang],
Chellappa, R.[Rama],
Zheng, Q.F.[Qin-Fen],
Robust structure from motion estimation using inertial data,
JOSA-A(18), No. 12, December 2001, pp. 2982-2997.
WWW Link.
0201
BibRef
Earlier: A1, A3, A2:
Reduction of Inherent Ambiguities in Structure from Motion Problem
Using Inertial Data,
ICIP00(Vol I: 204-207).
IEEE DOI
0008
BibRef
Qian, G.[Gang],
Chellappa, R.,
Zheng, Q.F.[Qin-Fen],
Bayesian structure from motion using inertial information,
ICIP02(III: 425-428).
IEEE DOI
0210
Use inertial guidance info to help in the SfM solution.
BibRef
Qian, G.,
Kale, A.,
Chellappa, R.,
Robust Estimation of Motion and Structure Using a Discrete h8 Filter,
ICIP00(Vol III: 616-619).
IEEE DOI
0008
BibRef
Qian, G.,
Chellappa, R.,
Zheng, Q.F.,
Ortolf, J.,
Camera Motion Estimation Using Monocular Image Sequences and Inertial Data,
UMD--TR3997, March 1999.
WWW Link.
BibRef
9903
Qian, G.[Gang],
Chellappa, R.,
Zheng, Q.F.[Qin-Fen],
Bayesian Algorithms for Simultaneous Structure From Motion Estimation
of Multiple Independently Moving Objects,
IP(14), No. 1, January 2005, pp. 94-109.
IEEE DOI
0501
BibRef
Earlier:
Robust bayesian cameras motion estimation using random sampling,
ICIP04(II: 1361-1364).
IEEE DOI
0505
BibRef
Earlier:
A bayesian approach to simultaneous motion estimation of multiple
independently moving objects,
ICPR02(III: 309-314).
IEEE DOI
0211
BibRef
Qian, G.[Gang],
Chellappa, R.[Rama],
Structure from Motion Using Sequential Monte Carlo Methods,
IJCV(59), No. 1, August 2004, pp. 5-31.
DOI Link
0404
BibRef
Earlier:
ICCV01(II: 614-621).
IEEE DOI
0106
Random sampling.
BibRef
Kaminski, J.Y.[Jeremy Yirmeyahu],
Teicher, M.[Mina],
A General Framework for Trajectory Triangulation,
JMIV(21), No. 1, July 2004, pp. 27-41.
DOI Link
0409
BibRef
Earlier:
General Trajectory Triangulation,
ECCV02(II: 823 ff.).
Springer DOI
0205
Stereo with motion and non-synchronized cameras.
Use the trajectory.
BibRef
Kim, J.S.[Jun-Sik],
Hwangbo, M.[Myung],
Kanade, T.[Takeo],
Spherical approximation for multiple cameras in motion estimation:
Its applicability and advantages,
CVIU(114), No. 10, October 2010, pp. 1068-1083.
Elsevier DOI
1003
Camera motion estimation; Multiple cameras; Spherical approximation;
Camera calibration; Structure from motion
BibRef
Zhang, Q.L.[Qi-Long],
Pless, R.,
Fusing video and sparse depth data in structure from motion,
ICIP04(V: 3403-3406).
IEEE DOI
0505
BibRef
Wan, A.S.K.,
Siu, A.M.K.,
Lau, R.W.H.,
Ngo, C.W.,
A robust method for recovering geometric proxy from multiple panoramic
images,
ICIP04(II: 1369-1372).
IEEE DOI
0505
3D motion from wide baseline cameras with noisy matches.
BibRef
Demirdjian, D.[David],
Horaud, R.[Radu],
A Projective Framework for Scene Segmentation in the Presence of Moving
Objects,
CVPR99(I: 2-8).
IEEE DOI Given a sequence of pairs, and the corresponding points, this is what you
can do.
BibRef
9900
Sparr, G.,
Lindström, P.,
Euclidean Reconstruction and Calibration from Known Placements of
Uncalibrated and Uncorrelated Cameras,
SCIA99(Computer Vision).
BibRef
9900
Sparr, G.[Gunnar],
Euclidean and Affine Structure/Motion for Uncalibrated Cameras from
Affine Shape and Subsidiary Information,
SMILE98(xx-yy).
BibRef
9800
Earlier:
Simultanious Reconstruction of Scene Structure and
Camera Locations from Uncalibrated Image Sequences,
ICPR96(I: 328-333).
IEEE DOI
9608
BibRef
Earlier:
A Common Framework for Kinetic Depth, Reconstruction and Motion for
Deformable Objects,
ECCV94(B:471-482).
Springer DOI (Lund Univ./LTH, S)
BibRef
Weinshall, D.[Daphna],
Anandan, P.,
Irani, M.[Michal],
From Ordinal to Euclidean Reconstruction with Partial Scene Calibration,
SMILE98(xx-yy).
BibRef
9800
Navab, N.,
Deriche, R., and
Faugeras, O.D.,
Recovering 3D Motion and Structure from Stereo and 2D
Token Tracking Cooperation,
ICCV90(513-516).
IEEE DOI Stereo and optical flow, using lines.
BibRef
9000
Waldmann, J.,
Merhav, S.,
Fusion of Stereo and Motion Vision for 3-D Reconstruction,
ICPR92(I:5-8).
IEEE DOI
BibRef
9200
Weng, J.,
Huang, T.S.,
Complete Structure and Motion from Two Monocular Sequences
without Stereo Correspondence,
ICPR92(I:651-654).
IEEE DOI
BibRef
9200
Gambotto, J.P.,
Determining Stereo Correspondences and Egomotion
from a Sequence of Stereo Images,
ICPR90(I: 259-262).
IEEE DOI Trinocular view, motion helps stereo helps motion.
BibRef
9000
Thacker, N.A.,
Zheng, Y., and
Blackbourn, R.,
Using a Combined Stereo/Temporal Matcher to Determine Ego-motion,
BMVC90(121-126).
PDF File. Matches based on second derivatives at corners.
BibRef
9000
Asada, M.[Minoru],
Tsuji, S.[Saburo],
Inferring Motion of Cylindrical Object from Shape Information,
IJCAI83(1032-1034).
BibRef
8300
And:
Inferring Motion of Cylindrical Object from Shading,
CVPR83(240-245).
Shading information is used to segment the scene (synthetic images
are used). The motion can be derived by matching.
(
See also Automatic Analysis of Moving Images. )
BibRef
Tsuji, S.,
Morizono, A.,
Kuroda, S.,
Understanding a Simple Cartoon Film by a Computer Vision System,
IJCAI77(609-610).
BibRef
7700
Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Motion Using Depth Information .