Direct least squares fitting of ellipses

Proceedings - International Conference on Pattern Recognition

Volumn 1, Issue , 1996, Pages 253-257

  Fitzgibbon, Andrew W ^a   Pilu, Maurizio ^a   Fisher, Robert B ^a  

^a UNIVERSITY OF EDINBURGH   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ALGEBRA; PATTERN RECOGNITION;

BAD DATA; EIGENSYSTEM; ITERATIVE REFINEMENT; LEAST SQUARES FITTING; NEW EFFICIENT METHOD; NORMALIZATION FACTORS; SCATTERED DATA;

GEOMETRY;

EID: 84898804083     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPR.1996.546029     Document Type: Conference Paper

References (22)

1. G.J.Agin. Representationanddescriptionofcurvedobjects. PhD thesis, AIM-173, Stanford AI Lab. 1972.
2. R. C. Bolles and M. A. Fischler. A RANSAC-basedapproach to model fitting and its application to finding cylinders in range data. In Proceedings, International Joint Conference on AI, pages 637-643.1981.
3. F. Bookstein. Fitting conic sections to scattered data. Computer Graphics and Image Processing, (9):56-71,1979.
4. T. Ellis, A. Abbood, and B. Brillault. Ellipse detection and matching with uncertainty. Image and Vision Computing, 10(2):271-276,1992.
5. A. Fitzgibbon and R. Fisher. A buyer's guide to conic fitting. In Proceedings of British Machine Vision Conference, Birmingam, 1995.
6. W. Gander, G. Golub, and R. Strebel. Least-square fitting of circles and ellipses. BIT, (43):558-578,1994.
7. R. M. Haralick and L. G. Shapiro. Computer and Robot Vision, volume 1. Addison-Wesley, 1993.
8. K. Kanatani. Statistical bias of conic fitting and renormaliz-ation. IEEE T-PAMI, 16(3):320-326,1994.
9. D. Keren, D. Cooper, and J. Subrahmonia. Describing complicated objects by implicit polynomials. IEEE T-PAMI, 16(l):38-53,1994.
10. V. Leavers. Shape Detection in Computer Vision Using the Hough Transform. Springer-Verlag, 1992.
11. K. A. Paton. Conic sections in automatic chromosome analysis. In B. Meltzer and D. Michie, editors. Machine Intelligence 5, pages 411-434. Edinburgh University Press, Edinburgh, 1969.
12. M. Pilu. Part-based Grouping and Recogntion: A Model-Guided Approach. PhD Thesis, Department of Artificial Intelligence, University of Edinburgh, Scotland, 1996. Jun, 1996.
13. J. Porrill. Fitting ellipses and predicting comfidence envelopes using a bias corrected Kalman filter. Image and Vision Computing, 8(1), Feb. 1990.
14. S. S. Rao. Optimization: Theory and Applications. Wiley Eastern, 2 edition, 1984.
15. P.Rosin. A note on the least square fitting of ellipses. Pattern Recognition Letters, (14):799-808. Oct. 1993.
16. P. Rosin and G. West. Segmenting curves into lines and arcs. In Proceedings of the Third International Conference on Computer Vision, pages 74-78, Osaka, Japan, Dec. 1990.
17. P. L. Rosin. Ellipse fitting by accumulating five-point fits. Pattern Recognition Letters, (14):661-699, Aug. 1993.
18. P. Sampson. Fitting conic sections to very scattered data: An iterative refinement of the Bookstein algorithm. Computer Graphics and Image Processing, (18):97-108,1982.
19. F. Solina and R. Bajcsy. Recovery of parametric models from range images: The case of superquadrics with global deformations. IEEE PAMI, 12(2), Feb. 1990.
20. G. Taubin. Estimation of planar curves, surfaces and non-planar space curves defined by implicit equations with applications to edge and range image segmentation. IEEE PAMI, 13(11):1115-1138,Nov. 1991.
21. J. H. Wilkinson. The algebraic eigenvalue problem. Claredon Press, Oxford, England, 1965.
22. H. K. Yuen, J. Illingworth, and J. Kittler. Detecting partially occluded ellipses using the Hough transform. Image and Vision Computing, 7(l):31-37,1989.