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References

1
N. Ayache. Artificial Vision for Mobile Robots: Stereo Vision and Multisensory Perception. MIT Press, Cambridge, MA, 1991.

2
J.V. Beck and K.J. Arnold. Parameter estimation in engineering and science. Wiley series in probability and mathematical statistics. J. Wiley, New York, 1977.

3
F. Bookstein. Fitting conic sections to scattered data. Computer Vision, Graphics, and Image Processing, 9:56-71, 1979.

4
C.K. Chui and G. Chen. Kalman Filtering with Real-Time Applications. Springer Ser. Info. Sci., Vol. 17. Springer, Berlin, Heidelberg, 1987.

5
W. Förstner. Reliability analysis of parameter estimation in linear models with application to mensuration problems in computer vision. Comput. Vision, Graphics Image Process., 40:273-310, 1987.

6
F.R. Hampel. Robust estimation: A condensed partial survey. Z. Wahrscheinlichkeitstheorie Verw. Gebiete, 27:87-104, 1973.

7
P.J. Huber. Robust Statistics. John Wiley & Sons, New York, 1981.

8
A.M. Jazwinsky. Stochastic Processes and Filtering Theory. Academic, New York, 1970.

9
K. Kanatani. Renormalization for unbiased estimation. In Proc. Fourth Int'l Conf. Comput. Vision, pages 599-606, Berlin, 1993.

10
Y.G. Leclerc. Constructing simple stable description for image partitioning. The International Journal of Computer Vision, 3(1):73-102, 1989.

11
M. Li. Minimum description length based 2D shape description. In Proceedings of the 4th Proc. International Conference on Computer Vision, pages 512-517, Berlin, Germany, May 1993. IEEE Computer Society Press.

12
D. G. Lowe. Review of ``TINA: The Sheffield AIVRU vision system'' by J. Porrill et al. In O. Khatib, J. Craig, and T. Lozano-Pérez, editors, The Robotics Review I, pages 195-198. MIT Press, Cambridge, MA, 1989.

13
S.J. Maybank. Filter based estimates of depth. In Proc. British Machine Vision Conf., pages 349-354, University of Oxford, London, UK, September 1990.

14
P.S. Maybeck. Stochastic Models, Estimation and Control, volume 1. Academic, New York, 1979.

15
P.S. Maybeck. Stochastic Models, Estimation and Control, volume 2. Academic, New York, 1982.

16
A. Papoulis. Probability, Random Variables, and Stochastic Processes. McGraw-Hill, New York, 1965.

17
J. Porrill. Fitting ellipses and predicting confidence envelopes using a bias corrected kalman filter. Image and Vision Computing, 8(1):37-41, 1990.

18
William J.J. Rey. Introduction to Robust and Quasi-Robust Statistical Methods. Springer, Berlin, Heidelberg, 1983.

19
J. Rissanen. Minimum description length principle. Encyclopedia of Statistic Sciences, 5:523-527, 1987.

20
P.L. Rosin. A note on the least squares fitting of ellipses. Pattern Recognition Letters, 14:799-808, 1993.

21
P.L. Rosin and G.A.W. West. Segmenting curves into elliptic arcs and straight lines. In Proc. Third Int'l Conf. Comput. Vision, pages 75-78, Osaka, Japan, 1990.

22
P.J. Rousseeuw and A.M. Leroy. Robust Regression and Outlier Detection. John Wiley & Sons, New York, 1987.

23
L.S. Shapiro. Affine Analysis of Image Sequences. PhD thesis, Dept. of Engineering Science, Oxford University, 1993.

24
Z. Zhang, R. Deriche, O. Faugeras, and Q.-T. Luong. A robust technique for matching two uncalibrated images through the recovery of the unknown epipolar geometry. Artificial Intelligence Journal, 1995. to appear. Also INRIA Research Report No.2273, May 1994.

25
Z. Zhang and O. Faugeras. 3D Dynamic Scene Analysis: A Stereo Based Approach. Springer, Berlin, Heidelberg, 1992.



Zhengyou Zhang
Thu Feb 8 11:42:20 MET 1996