A collection of references about camera motion estimation and kalman filtering, arranged in alphabetic order. The accumulated literature on camera motion estimation would choke a large horse. There were papers I wished I had found earlier, and treatments of optimal estimation that I wish I hadn't (and don't list here !) And never forget to look in Numerical Recipes!
The author links often turn up more recent work along the same lines...
If you have a favorite reference that you want to share with me, drop
me a note. Likewise if one of these links goes stale !
A.
Azarbayejani and A.
Pentland,
"Recursive Estimation of Motion, Structure, and Focal Length"
IEEE Trans. Pattern Analysis and Machine Intelligence, 1995?. S. M. Bozic, Digital and Kalman Filtering,
Edward Arnold Pub., London, 1994 (also 1979). Robert G. Brown and Patrick Y.H. Hwang, Introduction to
Random Signal Analysis and Kalman Filtering,
John Wiley & Sons, New York, Second Ed. 1992 T.J. Broida, S. Chandrashekhar,
R. Chellappa,
"Recursive 3-D Motion Estimation from a
Monocular Image Sequence", IEEE Transactions on
Aerospace and Electronic Systems, Vol. 26, No. 4, July 1990,
pp. 639-656.
Olivier Faugeras and
Bernard Mourrain, "On the geometry and
algebra of the point and line correspondences between N images",
Proceedings of ICCV95, pages 951-956.
Arthur Gelb, ed., Applied Optimal
Estimation, MIT Press, Cambridge, MA 1974.
Mohinder S. Grewal, Angus P. Andrews, Kalman Filtering:
Theory and Practice, Prentice-Hall, Englewood Cliffs,
New Jersey, 1993.
Berthold K.P. Horn,
"Closed-form solution of absolute orientation using unit
quaternions", Journal of the Optical Society of America, Vol 4,
No. 4, April 1987.
Berthold
K.P. Horn,and E.J. Weldon, Jr., "Direct Methods for Recovering
Motion", International Journal of Computer Vision, Vol. 2,
No. 1, pp. 51-76, June 1988.
Berthold K.P. Horn,
"Relative Orientation",
International Journal of Computer Vision,
Vol. 4, No. 1, pp. 59-78, 1990.
Andrew H. Jazwinski, Stochastic Processes and Filtering
Theory, Academic Press, New York, 1970. Ratnam V.R. Kumar, Arun Tirumalai, and
Ramesh C. Jain,
"A Non-linear Optimization Algorithm for the Estimation of Structure
and Motion Parameters", Proc. IEEE Conf. on Computer Vision and
Pattern Recognition, June 1989, pp. 136-143. J. Oliensis and J. Inigo Thomas, "Incorporating Motion Error in Multi-Frame
Structure from Motion", Proc. 1991 IEEE Workshop on Visual Motion,
Oct. 1991, Princeton, N.J., pp. 8-13. William H. Press, Saul A. Teukolsky, William T. Vetterling,
Brian P. Flannery,
Numerical Recipes in C: The Art of Scientific Computing
, 2nd edition, Cambridge Univ. Press, N.Y., 1992. S. Soatto,
P. Perona, R. Frezza, and G. Picci, "Recursive Motion and
Structure Estimation with Complete Error Characterization",
Proc. 1993. IEEE Conf. on Comp. Vision and Pattern Recog., pp. 428-433. Richard Szeliski and Sing Bing Kang, Recovering 3D
shape and motion from image streams using non-linear least
squares, CRL Technical Report 93/3, Digital Equipment Corp.,
Cambridge Research Labs, March 1993. Juyang Weng, Narendra
Ahuja, Thomas
S. Huang, Optimal motion and structure
estimation, in Proc. IEEE Trans. Pattern Analysis and
Machine Intelligence, 15(9), pp. 864-884, September 1993. If you have a favorite reference that you want to share with me, drop
me a note. Likewise if one of these links goes stale !
Also MIT Media Lab Vision & Modeling Group TR#243.
Bozic is often cited, but in my opinion, a mediocre treatment.
TK7872.F5.B7 in Barker Eng. Lib.
A necessary citation, but I preffered Jazwinski.
TK5102.5.B696 in Barker Eng. Lib.
This paper is THE one on using the IEKF to solve the camera motion
problem. I didn't use either their system or measurement model, however.
Actually, I included this one more for the author links than the paper
Again, this is one of those "must-cites" that I didn't find real useful.
Grewal and Andrews is truly one of the better books out there for
someone trying to implement a Kalman filter. You will want another
book for the theoretical underpinnings, and they strangely don't mention
Iterated Extended Kalman Filters at all. But they do have chapters on
different implementation methods for overcoming numerical instabilities and
how to go about taming a diverging filter.
QA402.3.G695 1993 in Barker Eng. Lib.
Berthold K.P. Horn,
Robot Vision, MIT Press, Cambridge, MA, 1986.
A good introduction to the mathematics behind the Kalman filter.
QA276.8.J42 in Barker Eng. Lib.
A Levenberg-Marquardt approach, with a continuous extension to the basic
batch algorithm. They don't try to determine
Z or f directly.
TA1632.I36 1989 in Barker Eng. Lib.
This paper presents an kalman filtering of parameters determined from
a two frame batch method. Oliensis has newer treatments online...
TJ211.4.W67 1991 in Barker Eng. Lib.
Truly an invaluable reference. Although it doesn't cover kalman
filtering, it did provide the matrix inversion and Levenberg-Marquardt
routines.
http://world.std.com/~nr
This paper discusses an approach where an Extended Kalman Filter is applied
to the output of a two frame batch estimator.
TA1632.I36 1993 in Barker Eng. Lib.
http://www.research.digital.com/CRL/abstracts/93.3.html
also in 1993 IEEE Conf. on Comp. Vision and Pattern Recog.
This paper compares a batch method,
using a Levenberg-Marquardt algorithm, with an IEKF approach. The
Lev.-Mar. method won ! It also contains a good discussion of the
noise issues which plague linear (epipolar) approaches.
An earlier/simpler version also appeared in Proc. IEEE Conf. on
Computer Vision and Pattern Recognition, pp. 144-152, June 1989.
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wad@media.mit.edu