Curve Correspondence in Two-Dimensional Space

Article Preview

Abstract:

Curve or contour correspondence has been extensively explored. Previous work was mainly concentrated on the rigid correspondence or alignment. This paper presents a spectral analysis method to resolve the problem of curves correspondence with non-rigid deformation. Using the embedding of original affinity matrix to the spectral domain, we can build the point correspondence of no-rigid deformation shapes.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

4651-4654

Citation:

Online since:

May 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Mokhtarian F, Mackworth A K. A theory of multiscale, curvature-based shape representation for planar curves[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14(8) (1992), pp.789-805.

DOI: 10.1109/34.149591

Google Scholar

[2] S. Abbassi, F. Mokhtarian, J. Kittler. Enhancing CSS-based shape retrieval for objects with shallow concavities. Image Vision Comput. , 18 (2000), p.199–211.

DOI: 10.1016/s0262-8856(99)00019-0

Google Scholar

[3] F. Mokhtarian, S. Abbasi. Shape similarity retrieval under affine transforms. Pattern Recognition, 35 (2002), p.31–41.

DOI: 10.1016/s0031-3203(01)00040-1

Google Scholar

[4] Carcassoni M, Hancock E R. Spectral correspondence for point pattern matching[J]. Pattern Recognition, 36(1) ( 2003), p, 193-204.

DOI: 10.1016/s0031-3203(02)00054-7

Google Scholar

[5] Jain V, Zhang H. Robust 3D shape correspondence in the spectral domain[C]. Shape Modeling and Applications, 2006. SMI 2006. IEEE International Conference on. IEEE( 2006), pp.19-19.

DOI: 10.1109/smi.2006.31

Google Scholar

[6] Zhang H, Van Kaick O, Dyer R. Spectral mesh processing[C] Computer graphics forum. Blackwell Publishing Ltd, 29(6) (2010), pp.1865-1894.

DOI: 10.1111/j.1467-8659.2010.01655.x

Google Scholar

[7] Zhang H, Van Kaick O, Dyer R. Spectral methods for mesh processing and analysis[C] Proceedings of Eurographics State-of-the-art Report. (2007), pp.1-22.

Google Scholar

[8] Kong, Weixin, and Benjamin B. Kimia. On solving 2D and 3D puzzles using curve matching., Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on. Vol. 2. IEEE(2001).

DOI: 10.1109/cvpr.2001.991015

Google Scholar

[9] Gruen, Armin, and Devrim Akca. Least squares 3D surface and curve matching., ISPRS Journal of Photogrammetry and Remote Sensing 59. 3 (2005), pp.151-174.

DOI: 10.1016/j.isprsjprs.2005.02.006

Google Scholar

[10] Frenkel, Max, and Ronen Basri. Curve matching using the fast marching method., Energy Minimization Methods in Computer Vision and Pattern Recognition. (Springer Berlin Heidelberg 2003).

DOI: 10.1007/978-3-540-45063-4_3

Google Scholar

[11] Kimmel R, Sethian J A. Fast marching methods for robotic navigation with constraints[J]. Center for Pure and Applied Mathematics Report, University of California, Berkeley (1996).

Google Scholar

[12] Reuter M, Biasotti S, Giorgi D, et al. Discrete Laplace–Beltrami operators for shape analysis and segmentation[J]. Computers & Graphics, 33(3) (2009), pp.381-390.

DOI: 10.1016/j.cag.2009.03.005

Google Scholar