Roach, J.W., and
Aggarwal, J.K.,
Determining the Movement of Objects from a Sequence of Images,
PAMI(2), No. 6, November 1980, pp. 554-562.
Motion, Rigidity Constraint. Two views of 6 points or 3 views of 4 points. But need more points
for accuracy. Non linear, uses rigidity, very sensitive to noise.
BibRef
8011
Aggarwal, J.K., and
Mitiche, A.[Amar],
Structure and Motion from Images,
DARPA85(89-95).
Consistency of rigid objects angles or distances. 5 points in 2
images for distances constant or 4 lines in 3 images for angles
constant.
BibRef
8500
Mitiche, A.[Amar],
Seida, S.[Steve], and
Aggarwal, J.K.,
Using Constancy of Distance to Estimate Position and
Displacement in Space,
PAMI(10), No. 4, July 1988, pp. 594-599.
IEEE DOI
BibRef
8807
Earlier:
Estimation of Position and Displacement in Space from Two
Images,
CVPR85(504-509).
Five (5) points in 2 images. Relies on distances in the two views
being the same (rigid objects). The position in space is derived
first then the potion parameters are derived from the positions.
BibRef
Mitiche, A.[Amar],
On Kineopsis and Computation of Structure and Motion,
PAMI(8), No. 1, January 1986, pp. 109-112.
BibRef
8601
And:
Correction:
PAMI(11), No. 5, May 1989, pp. 540-541.
IEEE Top Reference.
Motion, Structure. Central projection, it requires 4 points in 2 views for the motion
of rigid objects. The correction states that 5 rather than 4
points are required to determine structure and motion.
See also Computational Approach to the Fusion of Stereopsis and Kineopsis, A.
See also Three-Dimensional Space from Optical Flow Correspondence.
BibRef
Jerian, C.[Charles], and
Jain, R.C.[Ramesh C.],
Determining Motion Parameters for Scenes with Translation and Rotation,
PAMI(6), No. 4, July 1984, pp. 523-530.
BibRef
8407
Earlier:
Motion83(71-77).
Motion, FOE. Study of several methods to determine the camera rotation
parameters and FOE. The method combines the work of Jain and
Prazdny. Real scenes require better low-level processing.
BibRef
Bennett, B.M.,
Hoffman, D.D.,
Nicola, J.E., and
Prakash, C.,
Structure from Two Orthographic Views of Rigid Motion,
JOSA-A(6), No. 7, July 1989, pp. 1052-1069.
BibRef
8907
Kumar, R.V.R.,
Tirumalai, A.P., and
Jain, R.C.,
A Non-Linear Optimization Algorithm for the Estimation of
Structure and Motion Parameters,
CVPR89(136-143).
IEEE DOI Similar to the Kalman
(
See also Estimation of Object Motion Parameters from Noisy Images. ) filtering approaches, but minor
differences.
BibRef
8900
Netravali, A.N.,
Huang, T.S.,
Krishnakumar, A.S., and
Holt, R.J.,
Algebraic Methods in 3-D Motion Estimation from
Two-View Point Correspondences,
IJIST(1), No. 1, Summer 1989, pp. 78-99.
BibRef
8900
Holt, R.J.[Robert J.], and
Netravali, A.N.[Arun N.],
Optimum Rigid Motion with One Perspective View,
IJIST(4), No. 2, Summer 1992, pp. 123-129.
BibRef
9200
Philip, J.,
Estimation of Three-Dimensional Motion of Rigid
Objects from Noisy Observations,
PAMI(13), No. 1, January 1991, pp. 61-66.
IEEE DOI
BibRef
9101
And:
ISRN KTH/NA/P--89/02--SE.
BibRef
And:
Motion Parameters from an Occluded Rectangle,
ISRN KTH/NA/P--89/15--SE, 1989.
Builds on the Tsai and Huang
(
See also Uniqueness and Estimation of Three-Dimensional Motion Parameters of Rigid Objects with Curved Surfaces. ) work and similar to the pose estimation
paper of Arun. For more than 8 points in 2 views use a least
squares techniques to get the motion.
Similar to
See also Optimal Visual Motion Estimation: A Note.
BibRef
Philip, J.,
Motion Parameters from Right Angles,
JMIV(1), No. 2, 1992, pp. 107-120.
BibRef
9200
And:
ISRN KTH/NA/P--90/29--SE.
BibRef
Faugeras, O.D., and
Maybank, S.J.,
Motion from Point Matches: Multiplicity of Solutions,
IJCV(4), No. 3, 1990, pp. 225-246.
Springer DOI
BibRef
9000
Earlier:
Motion89(248-255).
One of the several papers studying the limits and the bounds on the
number of solutions for given numbers of points. In 2 frames there
are a lot.
BibRef
Maybank, S.J.,
Rigid Velocities Compatible with Five Image Velocity Vectors,
IVC(8), No. 1, February 1990, pp. 18-23.
Elsevier DOI
See also Algorithm for Analysing Optical Flow Based on the Least-Squares Method.
BibRef
9002
Longuet-Higgins, H.C.,
The Visual Ambiguity of a Moving Plane,
RoyalP(B-223), 1984, pp. 165-175.
BibRef
8400
And:
Multiple Interpretations of a Pair of Images of a Surface,
Royal(A-418), 1988, pp. 1-15.
Points.
See also Interpretation of a Moving Retinal Image, The.
See also Statistical Analysis of a Random Moving Surface, The.
See also Computer Algorithm for Reconstructing a Scene from Two Projections, A.
BibRef
Longuet-Higgins, H.C.,
Visual Motion Ambiguity,
Vision Research(26), No. 1, 1986, pp. 181-183.
BibRef
8600
Longuet-Higgins, H.C.,
A Computer Algorithm for Reconstructing a Scene from Two Projections,
Nature(293), No. 5828, 10 September 1981, pp. 133-135.
DOI Link
BibRef
8109
And:
RCV87(61-62)
BibRef
And:
The Reconstruction a Scene from Two Projections --
Configurations That Defeat the 8-Point Algorithm,
CAIA84(395-397).
BibRef
And:
Configurations That Defeat the 8-Point Algorithm,
IU84(173-177).
(Double check the initial reference, I have seen it differently:
Nature(317), 1985, pp. 314-319. Algorithm or Program in title?)
Eight points.
See also Multiple Interpretations of a Pair of Images of a Surface.
BibRef
Spetsakis, M.E., and
Aloimonos, Y.,
Optimal Visual Motion Estimation: A Note,
PAMI(14), No. 9, September 1992, pp. 959-964.
IEEE DOI
BibRef
9209
Earlier:
Optimal Motion Estimation,
Motion89(229-237).
Two methods for two frame motion estimation.
Says Aisbett (
See also Iterated Estimation of the Motion Parameters of a Rigid Body from Noisy Displacement Vectors, An. ) and Philip
(
See also Estimation of Three-Dimensional Motion of Rigid Objects from Noisy Observations. ) papers are similar techniques to this.
BibRef
Shashua, A.,
Projective Structure from Uncalibrated Images:
Structure-from-Motion and Recognition,
PAMI(16), No. 8, August 1994, pp. 778-790.
IEEE DOI
BibRef
9408
And:
MIT AI Memo-1363, September 1992.
WWW Link.
BibRef
Earlier:
Projective Depth: A Geometric Invariant for 3D Reconstruction from
Two Perspective/Orthographic Views and for Visual Recognition,
ICCV93(583-590).
IEEE DOI
BibRef
And:
A Geometric Invariant for Visual Recognition and 3D Reconstruction from
Two Perspective/Orthographic Views,
WQV93(107-117).
BibRef
And:
Projective Invariant and Structure from
Two Perspective/Orthographic Views: Motion and Recognition,
DARPA93(767-776).
3-D from 2 views.
See also Correspondence and Affine Shape from Two Orthographic Views: Motion and Recognition.
BibRef
Wolf, L.B.[Lior B.], and
Shashua, A.[Amnon],
Two-body Segmentation from Two Perspective Views,
CVPR01(I:263-270).
IEEE DOI
0110
Segment independently moving objects.
BibRef
Wolf, L.B.[Lior B.],
Shashua, A.[Amnon],
Affine 3-D Reconstruction from Two Projective Images of Independently
Translating Planes,
ICCV01(II: 238-244).
IEEE DOI
0106
Two views of planes.
BibRef
Shashua, A.[Amnon],
Correspondence and Affine Shape from Two Orthographic Views:
Motion and Recognition,
MIT AI Memo-1327, December 1991.
WWW Link.
BibRef
9112
Shashua, A.[Amnon],
Algebraic Functions for Recognition,
PAMI(17), No. 8, August 1995, pp. 779-789.
IEEE DOI
BibRef
9508
Earlier:
ARPA94(II:1029-1037).
BibRef
And:
MIT AI Memo-1452, January 1994.
Alignment based recognition.
WWW Link.
BibRef
Shashua, A.[Amnon],
Geometry and Photometry in 3D Visual Recognition,
MIT AI-TR-1401, November 1992.
WWW Link.
BibRef
9211
Shashua, A.[Amnon],
Geometric and Algebraic Aspects of 3D Affine and
Projective Structures from Perspective 2D Views,
MIT AI Memo-1405, July 1993.
WWW Link.
BibRef
9307
Shashua, A.,
On Photometric Issues in 3D Visual Recognition from a Single 2D Image,
IJCV(21), No. 1-2, January 1997, pp. 99-122.
DOI Link
9704
BibRef
Zhang, Z.Y.,
A Tighter Lower-Bound on the Spetsakis-Aloimonos Trilinear Constraints,
CVIU(67), No. 2, August 1997, pp. 202-204.
DOI Link
9708
BibRef
Zhuang, X.H.[Xin-Hua],
A Simplification to Linear Two-View Motion Algorithms,
CVGIP(46), No. 2, May 1989, pp. 175-178.
Elsevier DOI Simplify the 8 point approach.
BibRef
8905
Zhuang, X.H.[Xin-Hua],
Huang, T.S., and
Haralick, R.M.[Robert M.],
Two-View Motion Analysis: A Unified Algorithm,
JOSA-A(3), No. 9, September 1986, pp. 1492-1500.
BibRef
8609
Zhuang, X.H.[Xin-Hua], and
Haralick, R.M.,
Two View Motion Analysis,
CVPR85(686-690).
2 views of a single rigid body requires 6 point pairs.
BibRef
8500
Lee, C.H.[Chia-Hoang], and
Huang, T.S.,
Finding Point Correspondences and Determining Motion of a Rigid
Object from Two Weak Perspective Views,
CVGIP(52), No. 3, December 1990, pp. 309-327.
Elsevier DOI
BibRef
9012
Earlier:
CVPR88(398-403).
IEEE DOI Reduce n points to set of 4 point problems, determine underlying
motions and object structure. Coplanarity condition. Axis of
rotation tilt and scaling factor.
BibRef
Huang, T.S.,
Determining Three-Dimensional Motion and Structure from
Perspective Views,
HPRIP86(333-354).
BibRef
8600
Lee, C.H.[Chia-Hoang],
Structure and Motion from Two Perspective Views Via Planar Patch,
ICCV88(158-164).
IEEE DOI Motion from 4 points on a plane plus 2 points not on the plane.
BibRef
8800
Zhang, Z.Y.[Zheng-You],
Estimating Motion and Structure from Correspondences of
Line Segments between Two Perspective Images,
PAMI(17), No. 12, December 1995, pp. 1129-1139.
IEEE DOI
BibRef
9512
Earlier:
ICCV95(257-262).
IEEE DOI Claims to be the first to use line segments but many other papers use
line segments. Computes line matches using overlap of the lines, computes
motion by maximizing the overlap.
PS File.
BibRef
Pritt, M.D.,
Structure and Motion from Two Orthographic Views,
JOSA-A(13), No. 5, May 1996, pp. 916-921.
9605
BibRef
Salari, E.,
Jong, C.M.,
A Method to Calculate the Structure and Motion Parameters from
Line Correspondences,
PR(23), No. 6, 1990, pp. 553-561.
Elsevier DOI
BibRef
9000
Hartley, R.I.[Richard I.],
In Defense of the Eight-Point Algorithm,
PAMI(19), No. 6, June 1997, pp. 580-593.
IEEE DOI
9708
BibRef
Earlier:
In Defence of the 8-Point Algorithm,
ICCV95(1064-1070).
Award, ICCV Test of Time.
IEEE DOI
PDF File. Challanges the view that the 8-point algorithm is sensitive to
noise by preceding the algorithm with a normalization.
Provides an initial estimate of the fundamental matrix for iterative
methods.
BibRef
Isgrò, F.[Francesco],
Trucco, E.[Emanuele],
Robust estimation of motion, structure and focal length
from two views of a translating scene,
PRL(20), No. 8, August 1999, pp. 847-854.
BibRef
9908
Mühlich, M.[Matthias],
Mester, R.[Rudolf],
A considerable improvement in non-iterative homography estimation using
TLS and equilibration,
PRL(22), No. 11, September 2001, pp. 1181-1189.
Elsevier DOI
0108
BibRef
Zelnik-Manor, L.[Lihi],
Irani, M.[Michal],
Multiview Constraints on Homographies,
PAMI(24), No. 2, February 2002, pp. 214-223.
IEEE DOI
0202
BibRef
Earlier:
Multi-View Subspace Constraints on Homographies,
ICCV99(710-715).
IEEE DOI Motion of a planar surface.
Image motion of a planar surface between 2 camera views is
a homography (a 2D projective transformation).
Use constraints to derive linear constraints.
See also Multi-Frame Correspondence Estimation Using Subspace Constraints.
BibRef
Zelnik-Manor, L.[Lihi],
Irani, M.[Michal],
Multi-Frame Estimation of Planar Motion,
PAMI(22), No. 10, October 2000, pp. 1105-1116.
IEEE DOI
0011
BibRef
Earlier:
Multi-Frame Alignment of Planes,
CVPR99(I: 151-156).
IEEE DOI
BibRef
DARPA98(195-198).
Mosaic Generation.
Simultaneous multi-frame estimation, not pairwise.
BibRef
Chojnacki, W.[Wojciech],
Brooks, M.J.[Michael J.],
van den Hengel, A.J.[Anton J.],
Rationalising the Renormalisation Method of Kanatani,
JMIV(14), No. 1, February 2001, pp. 21-38.
DOI Link
0102
See also 3-D Interpretation of Optical-Flow by Renormalization.
See also Determining the Egomotion of an Uncalibrated Camera from Instantaneous Optical Flow.
BibRef
Chojnacki, W.[Wojciech],
Brooks, M.J.[Michael J.],
van den Hengel, A.J.[Anton J.],
Gawley, D.[Darren],
From FNS to HEIV:
A Link Between Two Vision Parameter Estimation Methods,
PAMI(26), No. 2, February 2004, pp. 264-268.
IEEE Abstract.
0402
BibRef
Earlier:
FNS and HEIV: relating two vision parameter estimation frameworks,
CIAP03(152-157).
IEEE DOI
0310
They are equivalent, solve the same thing differently.
Fundamental Numerical Scheme:
See also On the Fitting of Surfaces to Data with Covariances. HEIV:
See also Heteroscedastic Regression in Computer Vision: Problems with Bilinear Constraint. and
See also Estimation of Nonlinear Errors-in-Variables Models for Computer Vision Applications. Also:
See also Determining the Egomotion of an Uncalibrated Camera from Instantaneous Optical Flow.
BibRef
Chojnacki, W.[Wojciech],
Brooks, M.J.[Michael J.],
van den Hengel, A.J.[Anton J.],
Gawley, D.[Darren],
FNS, CFNS and HEIV: A Unifying Approach,
JMIV(23), No. 2, September 2005, pp. 175-183.
Springer DOI
0505
Unconstrained and constrained minimizers.
Extend analysis to more general cost functions.
BibRef
Chojnacki, W.[Wojciech],
Brooks, M.J.[Michael J.],
van den Hengel, A.J.[Anton J.],
Gawley, D.[Darren],
Revisiting Hartley's normalized eight-point algorithm,
PAMI(25), No. 9, September 2003, pp. 1172-1177.
IEEE Abstract.
0309
BibRef
Earlier:
A statistical rationalisation of Hartley's normalised eight-point
algorithm,
CIAP03(334-339).
IEEE DOI
0310
Evaluation of why Hartley's method works. The normalization improves
the conditioning of the matrix.
See also In Defense of the Eight-Point Algorithm.
See also On the Fitting of Surfaces to Data with Covariances.
BibRef
Chojnacki, W.[Wojciech],
Brooks, M.J.[Michael J.],
On the Consistency of the Normalized Eight-Point Algorithm,
JMIV(28), No. 1, May 2007, pp. 19-27.
Springer DOI
0710
BibRef
And:
A Consistency Result for the Normalized Eight-Point Algorithm,
CIAP07(603-608).
IEEE DOI
0709
BibRef
Chojnacki, W.[Wojciech],
van den Hengel, A.J.[Anton J.],
A dimensionality result for multiple homography matrices,
ICCV11(2104-2109).
IEEE DOI
1201
BibRef
Shen, C.H.[Chun-Hua],
Brooks, M.J.[Michael J.],
van den Hengel, A.J.[Anton J.],
Fast Global Kernel Density Mode Seeking:
Applications to Localization and Tracking,
IP(16), No. 5, May 2007, pp. 1457-1469.
IEEE DOI
0704
BibRef
Earlier:
Fast Global Kernel Density Mode Seeking with Application to
Localisation and Tracking,
ICCV05(II: 1516-1523).
IEEE DOI
0510
BibRef
Earlier:
Augmented Particle Filtering for Efficient Visual Tracking,
ICIP05(III: 856-859).
IEEE DOI
0512
BibRef
Shen, C.H.[Chun-Hua],
van den Hengel, A.J.,
Brooks, M.J.,
Visual Tracking via Efficient Kernel Discriminant Subspace Learning,
ICIP05(II: 590-593).
IEEE DOI
0512
BibRef
Shen, C.H.[Chun-Hua],
Kim, J.[Junae],
Wang, H.Z.[Han-Zi],
Generalized Kernel-Based Visual Tracking,
CirSysVideo(20), No. 1, January 2010, pp. 119-130.
IEEE DOI
1002
BibRef
Nister, D.,
An Efficient Solution to the Five-Point Relative Pose Problem,
PAMI(26), No. 6, June 2004, pp. 756-777.
IEEE Abstract.
0404
BibRef
CVPR03(II: 195-202).
IEEE DOI
0307
Find the possible solutions for relative camera motion between two
calibrated views given five corresponding points.
Compute the coefficients of a tenth degree polynomial and
find its roots.
BibRef
Nistér, D.[David],
Stewénius, H.[Henrik],
A Minimal Solution to the Generalised 3-Point Pose Problem,
JMIV(27), No. 1, January 2007, pp. 67-79.
Springer DOI
0702
BibRef
Earlier: A1 only:
CVPR04(I: 560-567).
IEEE DOI
0408
BibRef
Stewenius, H.[Henrik],
Nister, D.[David],
Kahl, F.[Fredrik],
Schaffalitzky, F.[Frederik],
A Minimal Solution for Relative Pose with Unknown Focal Length,
IVC(26), No. 7, 2 July 2008, pp. 871-877.
Elsevier DOI
0804
BibRef
Earlier:
CVPR05(II: 789-794).
IEEE DOI
0507
Relative pose; Relative orientation; Camera calibration
See also Recent developments on direct relative orientation.
BibRef
Stewenius, H.[Henrik],
Simplified Vehicle Calibration Using Multilinear Constraints,
SCIA03(669-676).
Springer DOI
0310
BibRef
Goshen, L.[Liran],
Shimshoni, I.[Ilan],
Anandan, P.,
Keren, D.[Daniel],
Motion Recovery by Integrating over the Joint Image Manifold,
IJCV(65), No. 3, December 2005, pp. 131-145.
Springer DOI
0601
BibRef
Earlier:
Recovery of epipolar geometry as a manifold fitting problem,
ICCV03(1321-1328).
IEEE DOI
0311
Recovery when motion is small.
BibRef
Mandel, Z.,
Shimshoni, I.,
Keren, D.,
Multi-Camera Topology Recovery from Coherent Motion,
ICDSC07(243-250).
IEEE DOI
0709
BibRef
Keren, D.[Daniel],
Shimshoni, I.[Ilan],
Goshen, L.[Liran],
Werman, M.[Michael],
All Points Considered: A Maximum Likelihood Method for Motion Recovery,
WTRCV02(155-160).
0204
BibRef
Thorup, A.[Anders],
How Did the Camera Move?,
CommAlgebra(31), No. 8, 2003, pp. 4097-4108.
WWW Link. Given 5 points in 3-space and two snapshots of these points, taken
with a camera at two different positions. Then, in general, there are
10 possibilities for the second position of the camera relative to its
first position. The result is well known. We prove it using the
Thom-Porteous Formula.
Proof of the Kruppa results.
(
See also Zur Ermittlung eines Objektes aus zwei Perspektiven mit innerer Orientierung. )
BibRef
0300
Laksov, D.[Dan],
Thorup, A.[Anders],
Wronski Systems for Families of Local Complete Intersection Curves,
CommAlgebra(31), No. 8, 2003, pp. 4007-4035.
WWW Link.
BibRef
0300
Schreiber, R.[Robert],
Li, Z.Y.[Ze-Yu],
Baker, H.[Harlyn],
Robust Software for Computing Camera Motion Parameters,
JMIV(33), No. 1, January 2009, pp. xx-yy.
Springer DOI
0804
Revisit:
See also Uniqueness and Estimation of Three-Dimensional Motion Parameters of Rigid Objects with Curved Surfaces. Analyze errors and how to fix them.
BibRef
Kalantari, M.[Mahzad],
Hashemi, A.[Amir],
Jung, F.[Franck],
Guedon, J.P.[Jean-Pierre],
A New Solution to the Relative Orientation Problem Using Only 3 Points
and the Vertical Direction,
JMIV(39), No. 3, March 2011, pp. 259-268.
WWW Link.
1103
BibRef
Kalantari, M.[Mahzad],
Jung, F.[Franck],
Guedon, J.P.[Jean-Pierre],
Paparoditis, N.[Nicolas],
The Five Points Pose Problem: A New and Accurate Solution Adapted to
Any Geometric Configuration,
PSIVT09(215-226).
Springer DOI
0901
BibRef
Hartley, R.I.[Richard I.],
Li, H.D.[Hong-Dong],
An Efficient Hidden Variable Approach to Minimal-Case Camera Motion
Estimation,
PAMI(34), No. 12, December 2012, pp. 2303-2314.
IEEE DOI
1210
2 view 5 point, 6 point focal length problem.
BibRef
Basta, T.[Tayeb],
Flaws in the Computer Algorithm for Reconstructing a Scene
from Two Projections,
IJMLC(2), No. 3, 2012, pp. 244-247.
DOI Link
1411
See also Computer Algorithm for Reconstructing a Scene from Two Projections, A.
BibRef
Özyesil, O.[Onur],
Singer, A.[Amit],
Basri, R.[Ronen],
Stable Camera Motion Estimation Using Convex Programming,
SIIMS(8), No. 2, 2015, pp. 1220-1262.
DOI Link
1507
BibRef
Saurer, O.[Olivier],
Vasseur, P.[Pascal],
Boutteau, R.,
Demonceaux, C.[Cedric],
Pollefeys, M.,
Fraundorfer, F.[Friedrich],
Homography Based Egomotion Estimation with a Common Direction,
PAMI(39), No. 2, February 2017, pp. 327-341.
IEEE DOI
1702
BibRef
Earlier: A1, A2, A4, A6, Only:
A Homography Formulation to the 3pt Plus a Common Direction Relative
Pose Problem,
ACCV14(II: 288-301).
Springer DOI
1504
Cameras
BibRef
Kang, L.[Lai],
Wu, L.[Lingda],
Wei, Y.M.[Ying-Mei],
Lao, S.Y.[Song-Yang],
Yang, Y.H.[Yee-Hong],
Two-view underwater 3D reconstruction for cameras with unknown poses
under flat refractive interfaces,
PR(69), No. 1, 2017, pp. 251-269.
Elsevier DOI
1706
Structure, and, Motion, (SaM)
BibRef
Earlier: A1, A2, A5, Only:
Two-View Underwater Structure and Motion for Cameras under Flat
Refractive Interfaces,
ECCV12(IV: 303-316).
Springer DOI
1210
BibRef
Shen, Y.[Yan],
Dai, Y.X.[Yu-Xing],
Structure from motion with efficient homography-based line matching,
JOSA-A(35), No. 2, February 2018, pp. 200-209.
DOI Link
1804
Machine vision, Optical flow, Three-dimensional sensing
BibRef
Rockwell, C.[Chris],
Johnson, J.[Justin],
Fouhey, D.F.[David F.],
The 8-Point Algorithm as an Inductive Bias for Relative Pose
Prediction by ViTs,
3DV22(1-11)
IEEE DOI
2408
Computer architecture, Performance gain, Prediction algorithms,
Transformers, Camera Pose, Vision Transformer, Eight Point Algorithm
BibRef
da Silveira, T.L.T.[Thiago L. T.],
Jung, C.R.[Claudio R.],
Perturbation Analysis of the 8-Point Algorithm:
A Case Study for Wide FoV Cameras,
CVPR19(11749-11758).
IEEE DOI
2002
BibRef
Fredriksson, J.[Johan],
Larsson, V.[Viktor],
Olsson, C.[Carl],
Practical robust two-view translation estimation,
CVPR15(2684-2690)
IEEE DOI
1510
BibRef
Nozawa, K.[Kazuki],
Torii, A.[Akihiko],
Okutomi, M.[Masatoshi],
Stable Two View Reconstruction Using the Six-Point Algorithm,
ACCV12(IV:122-135).
Springer DOI
1304
BibRef
Chi, Y.T.[Yu-Tseh],
Ho, J.[Jeffrey],
Yang, M.H.[Ming-Hsuan],
A Direct Method for Estimating Planar Projective Transform,
ACCV10(II: 268-281).
Springer DOI
1011
Planar projective transform (homography) from 2 images.
BibRef
Reisner-Kollmann, I.[Irene],
Reichinger, A.[Andreas],
Purgathofer, W.[Werner],
3D Camera Pose Estimation Using Line Correspondences and 1D
Homographies,
ISVC10(II: 41-52).
Springer DOI
1011
BibRef
Hedborg, J.[Johan],
Forssen, P.E.[Per-Erik],
Felsberg, M.[Michael],
Ringaby, E.[Erik],
Rolling shutter bundle adjustment,
CVPR12(1434-1441).
IEEE DOI
1208
BibRef
Earlier: A1, A4, A2, A3:
Structure and motion estimation from rolling shutter video,
IWMV11(17-23).
IEEE DOI
1201
BibRef
Grelsson, B.[Bertil],
Felsberg, M.[Michael],
Probabilistic Hough Voting for Attitude Estimation from Aerial Fisheye
Images,
SCIA13(478-488).
Springer DOI
1311
BibRef
Grelsson, B.[Bertil],
Felsberg, M.[Michael],
Isaksson, F.[Folke],
Efficient 7D aerial pose estimation,
WORV13(88-95)
IEEE DOI
1307
BibRef
Hedborg, J.[Johan],
Felsberg, M.[Michael],
Fast iterative five point relative pose estimation,
WORV13(60-67)
IEEE DOI
1307
cameras
BibRef
Hedborg, J.[Johan],
Forssén, P.E.[Per-Erik],
Felsberg, M.[Michael],
Fast and Accurate Structure and Motion Estimation,
ISVC09(I: 211-222).
Springer DOI
0911
Relative pose, 5 points.
BibRef
Batra, D.,
Nabbe, B.,
Hebert, M.,
An Alternative Formulation for Five Point Relative Pose Problem,
Motion07(21-21).
IEEE DOI
0702
BibRef
Li, H.D.[Hong-Dong],
Hartley, R.I.[Richard I.],
Five-Point Motion Estimation Made Easy,
ICPR06(I: 630-633).
IEEE DOI
0609
BibRef
Wu, F.C.,
Hu, Z.Y.,
Duan, F.Q.,
8-Point Algorithm Revisited: Factorized 8-Point Algorithm,
ICCV05(I: 488-494).
IEEE DOI
0510
Decompose into 2, introduce auxillary variables and solve linear equations.
BibRef
Schindler, K.[Konrad],
Suter, D.[David],
Two-View Multibody Structure-and-Motion with Outliers through Model
Selection,
PAMI(28), No. 6, June 2006, pp. 983-995.
IEEE DOI
0605
BibRef
Earlier:
Two-View Multibody Structure-and-Motion with Outliers,
CVPR05(II: 676-683).
IEEE DOI
0507
Multiple objects, 2 views. Given the correspondences (with errors).
Solve through Monte-Carlo sampling and analysis of the resulting motion
models.
BibRef
Schindler, K.[Konrad],
Suter, D.[David],
Wang, H.Z.[Han-Zi],
A Model-Selection Framework for Multibody Structure-and-Motion of Image
Sequences,
IJCV(79), No. 2, August 2008, pp. xx-yy.
Springer DOI
0711
BibRef
Schindler, K.[Konrad],
U, J.[James],
Wang, H.Z.[Han-Zi],
Perspective n-View Multibody Structure-and-Motion Through Model
Selection,
ECCV06(I: 606-619).
Springer DOI
0608
BibRef
Bartoli, A.E.[Adrien E.],
Hartley, R.I.,
Kahl, F.[Fredrik],
Motion from 3D Line Correspondences: Linear and Non-Linear Solutions,
CVPR03(I: 477-484).
IEEE DOI
0307
problem of aligning two reconstructions of lines and cameras in
projective, affine, metric or Euclidean space.
See also Motion Estimation for Nonoverlapping Multicamera Rigs: Linear Algebraic and L_infty Geometric Solutions.
BibRef
Trajkovic, M.[Miroslav],
Hedley, M.[Mark],
Rigid Motion Recovery From Less Than Eight Feature Point Matches,
BMVC97(xx-yy).
HTML Version.
0209
BibRef
And:
A practical algorithm for structure and motion recovery from long
sequence of images,
CIAP97(I: 470-477).
Springer DOI
9709
BibRef
Oliensis, J.[John],
Rigorous Bounds for Two-Frame Structure from Motion,
ECCV96(II:184-195).
Springer DOI
BibRef
9600
And:
TRNEC, October 1995.
PS File. Rotation from two frames.
See also Critique of Structure-from-Motion Algorithms, A.
BibRef
Oliensis, J.[John],
Genc, Y.[Yacup],
Three New Algorithms for 2-Image and >= 2-Image Structure from Motion,
TRNEC, August 2001.
PS File.
PDF File.
BibRef
0108
Earlier:
New Algorithms for Two-Frame Structure from Motion,
ICCV99(737-744).
IEEE DOI
See also Fast and Accurate Algorithms for Projective Multi-Image Structure from Motion.
BibRef
Schaffalitzky, F.,
Zisserman, A.,
Hartley, R.I.,
A Six Point Solution for Structure and Motion,
ECCV00(I: 632-648).
Springer DOI
PDF File.
0003
BibRef
Kaucic, R.[Robert],
Hartley, R.I.[Richard I.],
Dano, N.Y.[Nicolas Y.],
Plane-based Projective Reconstruction,
ICCV01(I: 420-427).
IEEE DOI
PDF File.
0106
BibRef
Hartley, R.I.[Richard I.],
Dano, N.Y.[Nicolas Y.],
Reconstruction from Six-Point Sequences,
CVPR00(II: 480-486).
IEEE DOI
PDF File.
0005
BibRef
Forsyth, D.A.,
Ioffe, S.,
Haddon, J.,
Bayesian Structure from Motion,
ICCV99(660-665).
IEEE DOI Sample the posterior distribution to find the
structure.
BibRef
9900
Lee, C.N.[Chia-Nan],
Haralick, R.M., and
Zhuang, X.,
Recovering 3-D Motion Parameters from Image Sequences
with Gross Errors,
Motion89(46-53).
Motion, Estimation Evaluation.
BibRef
8900
Martinez, J.M.,
Zhang, Z.,
Montano, L.,
Segment-Based Structure from an Imprecisely Located Moving Camera,
SCV95(182-187).
IEEE DOI Univeristy of Zaragoza. INRIA.
Accumulate the structure using line segment matches through the sequence.
BibRef
9500
Cipolla, R.,
Åström, K.E.,
Giblin, P.J.,
Motion from the Frontier of Curved Surfaces,
ICCV95(269-275).
IEEE DOI or:
HTML Version. Matching contours, determine the camera motion.
BibRef
9500
Aloimonos, Y.[Yi-Fannis (John)], and
Brown, C.M.[Christopher M.],
Direct Processing of Curvilinear Sensor Motion from a Sequence
of Perspective Images,
CVWS84(72-77).
Computation of the camera motion in general, without optical flow,
using constraints on the object in view.
BibRef
8400
Lee, C.Y.,
Cooper, D.B., and
Keren, D.,
Computing Correspondence Based on Regions and Invariants without
Feature Extraction and Segmentation,
CVPR93(655-656).
IEEE DOI Match small areas of the
images and generate affine transforms for the separate areas.
BibRef
9300
Lee, C.Y., and
Cooper, D.B.,
Structure and Motion from Region Correspondences and Affine Invariants,
DARPA93(707-711).
BibRef
9300
And:
CRA93(xx-yy).
Find motion as affine transforms of regions.
BibRef
Chen, S.S.,
Dynamic Scene Analysis and the 8-Point Algorithm,
ICPR88(I: 152-154).
IEEE DOI
BibRef
8800
Svensson, L., and
Naeve, A.,
Estimating the N-Dimensional Motion of an (N-1)-Dimensional Hyperplane
from Two Matched Images of N+1 Points,
SCIA87(605-622).
BibRef
8700
And:
ISRN KTH/NA/P-87/08-SE.
BibRef
Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Univ. of Illinois Parameter Estimation Papers .