16.2.1 Motion Estimates Using 2 Frames

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 Abstract. IEEE Top Reference.
WWW Version. 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. 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., and Jain, R.C.,
A Non-Linear Optimization Algorithm for the Estimation of Structure and Motion Parameters,
CVPR89(136-143).
IEEE Abstract. IEEE Top Reference. 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 Abstract. IEEE Top Reference.
WWW Version. 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. 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.
WWW Version. 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. 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), September 1981, pp. 133-135. BibRef 8109
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. BibRef

Spetsakis, M.E., and Aloimonos, Y.,
Optimal Visual Motion Estimation: A Note,
PAMI(14), No. 9, September 1992, pp. 959-964.
IEEE Abstract. IEEE Top Reference.
WWW Version. 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 Abstract. IEEE Top Reference.
WWW Version. BibRef 9408
And: MIT AI Memo-1363, September 1992.
WWW Version. BibRef
Earlier:
Projective Depth: A Geometric Invariant for 3D Reconstruction from Two Perspective/Orthographic Views and for Visual Recognition,
ICCV93(583-590).
WWW Version. 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.], Shashua, A.[Amnon],
Affine 3-D Reconstruction from Two Projective Images of Independently Translating Planes,
ICCV01(II: 238-244).
WWW Version. 0106Two 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 Version. BibRef 9112

Shashua, A.[Amnon],
Algebraic Functions for Recognition,
PAMI(17), No. 8, August 1995, pp. 779-789.
IEEE Abstract. IEEE Top Reference.
WWW Version. BibRef 9508
Earlier: ARPA94(II:1029-1037). BibRef
And: MIT AI Memo-1452, January 1994. Alignment based recognition.
WWW Version. BibRef

Shashua, A.[Amnon],
Geometry and Photometry in 3D Visual Recognition,
MIT AI-TR-1401, November 1992.
WWW Version. 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 Version. 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.
WWW Version. 9704 BibRef

Zhang, Z.Y.,
A Tighter Lower-Bound on the Spetsakis-Aloimonos Trilinear Constraints,
CVIU(67), No. 2, August 1997, pp. 202-204. 9708
WWW Version. BibRef

Zhuang, X.,
A Simplification to Linear Two-View Motion Algorithms,
CVGIP(46), No. 2, May 1989, pp. 175-178.
WWW Version. 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.
WWW Version. BibRef 9012
Earlier: CVPR88(398-403).
IEEE Abstract. IEEE Top Reference. 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 Abstract. IEEE Top Reference. 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 Abstract. IEEE Top Reference.
WWW Version. BibRef 9512
Earlier: ICCV95(257-262).
WWW Version.
WWW Version. 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.
Postscript Version. 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.
WWW Version. BibRef 9000

Hartley, R.I.[Richard I.],
In Defense of the Eight-Point Algorithm,
PAMI(19), No. 6, June 1997, pp. 580-593.
IEEE Abstract. IEEE Top Reference.
WWW Version. 9708 BibRef
Earlier:
In Defence of the 8-Point Algorithm,
ICCV95(1064-1070).
WWW Version.
WWW Version.
PDF Version. 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.
HTML Version. 0108 BibRef

Zelnik-Manor, L.[Lihi], Irani, M.[Michal],
Multiview Constraints on Homographies,
PAMI(24), No. 2, February 2002, pp. 214-223.
IEEE Abstract. IEEE Top Reference.
WWW Version. 0202 BibRef
Earlier:
Multi-View Subspace Constraints on Homographies,
ICCV99(710-715).
WWW Version. 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 Abstract. IEEE Top Reference.
WWW Version. 0011 BibRef
Earlier:
Multi-Frame Alignment of Planes,
CVPR99(I: 151-156).
IEEE Abstract. IEEE Top Reference.
WWW Version. 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.
WWW Version. 0102 See also 3-D Interpretation of Optical-Flow by Renormalization. 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. IEEE Top Reference. 0402 BibRef
Earlier:
FNS and HEIV: relating two vision parameter estimation frameworks,
CIAP03(152-157).
IEEE Abstract. IEEE Top Reference. 0310They 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

Brooks, M.J., Chojnacki, W., van den Hengel, A.J., Baumela, L.,
Robust Techniques for the Estimation of Structure from Motion in the Uncalibrated Case,
ECCV98(I: 281).
WWW Version. BibRef 9800

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.
WWW Version. 0505Unconstrained 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. IEEE Top Reference. 0309 BibRef
Earlier:
A statistical rationalisation of Hartley's normalised eight-point algorithm,
CIAP03(334-339).
IEEE Abstract. IEEE Top Reference. 0310Evaluation of why Hartley's method works. The normalization improves the conditioning of the matrix. See also In Defense of the Eight-Point Algorithm. BibRef

Brooks, M.J.[Michael J.], Chojnacki, W.[Wojciech], Gawley, D.[Darren], van den Hengel, A.J.[Anton J.],
What Value Covariance Information in Estimating Vision Parameters?,
ICCV01(I: 302-308).
WWW Version. 0106 BibRef

Chojnacki, W., Brooks, M.J., van den Hengel, A.J., Gawley, D.,
Estimating Vision Parameters given Data with Covariances,
BMVC00(xx-yy).
PDF Version. 0009 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.
WWW Version. 0710 BibRef
And:
A Consistency Result for the Normalized Eight-Point Algorithm,
CIAP07(603-608).
WWW Version. 0709 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.
WWW Version. 0704 BibRef
Earlier:
Fast Global Kernel Density Mode Seeking with Application to Localisation and Tracking,
ICCV05(II: 1516-1523).
WWW Version. 0510 BibRef
Earlier:
Augmented Particle Filtering for Efficient Visual Tracking,
ICIP05(III: 856-859).
WWW Version. 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).
WWW Version. 0512 BibRef

Nister, D.,
An Efficient Solution to the Five-Point Relative Pose Problem,
PAMI(26), No. 6, June 2004, pp. 756-777.
IEEE Abstract. IEEE Top Reference. 0404 BibRef CVPR03(II: 195-202).
IEEE Abstract. IEEE Top Reference. 0307Find 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.
WWW Version. 0702 BibRef
Earlier: A1 only: CVPR04(I: 560-567).
IEEE Abstract. IEEE Top Reference. 0408 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.
WWW Version. 0601 BibRef
Earlier:
Recovery of epipolar geometry as a manifold fitting problem,
ICCV03(1321-1328).
WWW Version. 0311Recovery when motion is small. 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 Version. 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 Version. BibRef 0300

Li, H.D.[Hong-Dong], Hartley, R.I.[Richard I.],
Five-Point Motion Estimation Made Easy,
ICPR06(I: 630-633).
WWW Version. 0609 BibRef

Wu, F.C., Hu, Z.Y., Duan, F.Q.,
8-Point Algorithm Revisited: Factorized 8-Point Algorithm,
ICCV05(I: 488-494).
WWW Version. 0510Decompose 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.
WWW Version. 0605 BibRef
Earlier:
Two-View Multibody Structure-and-Motion with Outliers,
CVPR05(II: 676-683).
WWW Version. 0507Multiple 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.
WWW Version. 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).
WWW Version. 0608 BibRef

Bartoli, A., Hartley, R.I., Kahl, F.[Fredrik],
Motion from 3D Line Correspondences: Linear and Non-Linear Solutions,
CVPR03(I: 477-484).
IEEE Abstract. IEEE Top Reference. 0307problem of aligning two reconstructions of lines and cameras in projective, affine, metric or Euclidean space. 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).
WWW Version. 9709 BibRef

Oliensis, J.[John],
Rigorous Bounds for Two-Frame Structure from Motion,
ECCV96(II:184-195).
WWW Version. BibRef 9600
And: TRNEC, October 1995.
Postscript Version. Rotation from two frames. BibRef

Oliensis, J.[John], Genc, Y.[Yacup],
Three New Algorithms for 2-Image and >= 2-Image Structure from Motion,
TRNEC, August 2001.
Postscript Version.
PDF Version. BibRef 0108
Earlier:
New Algorithms for Two-Frame Structure from Motion,
ICCV99(737-744).
WWW Version. 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).
WWW Version.
PDF Version. 0003 BibRef

Hartley, R.I.[Richard I.], Dano, N.Y.[Nicolas Y.],
Reconstruction from Six-Point Sequences,
CVPR00(II: 480-486).
IEEE Abstract. IEEE Top Reference.
WWW Version.
PDF Version. 0005 BibRef

Forsyth, D.A., Ioffe, S., Haddon, J.,
Bayesian Structure from Motion,
ICCV99(660-665).
WWW Version. 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 Top Reference. 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).
WWW Version.
WWW Version. or:
HTML Version.
Postscript 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., 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).
WWW Version.
IEEE Top Reference. 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 .