Abstract
In this paper a novel cross correlation technique is proposed for shape matching between two similar objects. The proposed technique can not only evaluate the similarity between any two objects, but also has two distinct advantages compared to previous work: (1) the deformed articulated objects such as human being with different poses, can be matched very well; (2) the local feature extraction and correspondence can be established at the same time. The basic tool we used is the shape profile driven from the curvature map of the object profile. The cross correlation technique is applied to the shape profile of the two objects to evaluate their similarity. Filtering scheme is used to enhance the quality of both shape matching and extracted features. The invariant property, the robustness and the efficiency of the shape profile in shape matching and feature extraction are discussed.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Baroni, M., Barletta, G., Fantini, A., Toso, A., Fantini, F.: Assessing LV wall motion by frame-to-frame curvature matching and optical flow estimation. In: IEEE Proceedings Computers in Cardiology, pp. 477–480 (1991)
Belongie, S., Malik, J., Puzicha, J.: Shape matching and object recognition using shape contexts. IEEE Transactions Pattern Analysis and Machine Intelligence 24(4), 509–522 (2002)
Gavrila, D.M.: A bayesian, exemplar-based approach to hierachical shape matching. IEEE Transactions Pattern Analysis and Machine Intelligence 29(8), 1408–1421 (2007)
Ip, C.Y., Lapadat, D., Sieger, L., Regli, W.C.: Using shape distributions to compare solid models. In: Proc. 7th ACM Symp. on Solid Modeling and Applications, pp. 273–280 (2002)
Lee, S.M., Abbott, A.L., Clark, N.A., Araman, P.A.: A shape representation for planar curves by shape signature harmonic embedding. In: Proc. CVPR 2006, pp. 1940–1947 (2006)
Manay, S., Hong, B.W., Yezzi, A., Soatto, S.: Integral invariant signatures. In: Proc. ECCV 2004, pp. 87–99 (2004)
Mohanna, F., Mokhtarian, F.: An Efficient Active Contour Model Through Curvature Scale Space Filterin. Multimedia Tools and Applications 21(3), 225–242 (2003)
Mokhtarian, F., Mackworth, A.K.: A theory of Mutliscale, Curvature-Based Shape Representation for Planar Curves. IEEE Trans. Pattern Anal and Machine Intell. 14(8), 789–804 (1992)
Mokhtarian, F., Suomela, R.: Curvature Scale Space for Image Point Feature Detection. In: Proc. International Conference on Image Processing and its Applications, Manchester, UK, pp. 206–210 (1999)
Persoon, E., Fu, K.S.: Shape discrimination using Fourier descriptors. IEEE Transactions on Systems, Man and Cybernetics 7(3), 170–179 (1977)
Pitas, I.: Digital Image Processing algorithms and applications. Wiley, Chichester (2000)
Osada, R., Funkhouser, T., Chazelle, B., Dobkin, D.: Shape Distributions. ACM Transactions on Graphics 21(4), 807–832 (2002)
Xiao, P., Barnes, N., Caetano, T., Lieby, P.: An mrf and gaussian curvature based shape representation for shape matching. In: Proc. CVPR 2007, (BMG Workshop) (2007)
Zahn, G.T., Roskies, R.Z.: Fourier descriptors for plane closed curves. IEEE Transactions on Computers C-21(3), 269–281 (1972)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Liu, YJ., Chen, T., Chen, XY., Chang, T.K., Yuen, M.M.F. (2008). Planar Shape Matching and Feature Extraction Using Shape Profile. In: Chen, F., Jüttler, B. (eds) Advances in Geometric Modeling and Processing. GMP 2008. Lecture Notes in Computer Science, vol 4975. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79246-8_27
Download citation
DOI: https://doi.org/10.1007/978-3-540-79246-8_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-79245-1
Online ISBN: 978-3-540-79246-8
eBook Packages: Computer ScienceComputer Science (R0)