16.2.1 Motion Estimates Using 2 Frames

Chapter Contents (Back)
Motion, Two Frames. See also Stereo Analysis, Two Views. There is considerable overlap in techniques for the two view stereo papers. Motion analysis papers here are mostly concerned with estimation of camera parameters from a given number of feature matches, not creating surfaces or general 3-D reconstructions.

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).
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.[Zeyu], 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


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., 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.[Yiannis (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 .


Last update:Nov 18, 2017 at 20:56:18