Abstract
We address the problem of feature correspondences in images of coplanar ellipses with objective to benefit of robust ellipse fitting algorithm. The main difficulty is the lack of projective invariant points immediately available. Therefore, our key idea is to construct virtual line and point features using the property of tangent invariance under perspective projection. The proposed method requires first a robust detection of ellipse edge points to fit a parametric model on each ellipse. The feature lines are then obtained by computing the 4 bitangents to each couple of ellipses. The points are derived by considering the tangent points and the intersection points between bitangents. Results of experimental studies are presented to demonstrate the reliability and robustness of the feature extraction process. Subpixel accuracy is easily achieved. A real application to camera self-calibration is also described.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Ducottet, C., Fournel, T., Barat, C.: Scale-adaptive detection and local characterization of edges based on wavelet transform. Signal Processing 84, 2115–2137 (2004)
Fitzgibbon, A., Pilu, M., Fisher, R.B.: Direct Least Square Fitting of Ellipses. IEEE Trans. PAMI 21(5), 476–480 (1999)
Habert, L.: Computing bitangents for ellipses. In: Proc. 17th Canadian Conference on Computational Geometry (CCCG 2005), pp. 294-297 (2005)
Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision. Cambridge University Press, Cambridge (2002)
Schmid, C., Zisserman, A.: The geometry and matching of lines and curves over multiple views. International Journal on Computer Vision 40(3), 199–234 (2000)
Kaminski, J.Y., Shashua, A.: Multiple View Geometry of General Algebraic Curves. International Journal on Computer Vision 56(3), 195–219 (2004)
Kahl, F., Heyden, A.: Using Conic Correspondence in Two Images to Estimate the Epipolar Geometry. In: Proceedings of the International Conference on Computer Vision (1998)
Mudigonda, P.K., Jawahar, C.V., Narayanan, P.J.: Geometric Structure Computation from Conics. In: Proceedings of Indian Conference on Computer Vision, Graphics & Image Processing (2004)
Rothwell, C.A., Zisserman, A., Forsyth, D.A., Mundy, J.L.: Planar Object Recognition using Projective Shape Representation. International Journal on Computer Vision 16(1), 57–99 (1995)
Sampson, S.P.: Fitting conic sections to very scattered data: an iterative refinement of the Bookstein algorithm. Computer Graphics and Image Processing 18, 97–108 (1982)
Triggs, B.: Autocalibration from planar sequences. In: Proc. of the European Conference on Computer Vision, Freiburg, Germany (June 1998)
Wu, Y., Li, X., Wu, F., Hu, Z.: Coplanar circles, quasi-affine invariance and calibration. Image and Vision Computing 24(4), 319–326 (2006)
Zhang, Z.: A flexible new technique for camera calibration. IEEE Trans. PAMI 22, 1330–1334 (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Barat, C., Menudet, J.F., Louhichi, H., Fournel, T. (2006). Feature Correspondences from Multiple Views of Coplanar Ellipses. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2006. Lecture Notes in Computer Science, vol 4292. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11919629_38
Download citation
DOI: https://doi.org/10.1007/11919629_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-48626-8
Online ISBN: 978-3-540-48627-5
eBook Packages: Computer ScienceComputer Science (R0)