This Paper presents a very simple and efficient approach that not only performs almost as good as many state-of-the-art techniques but also scales up to large databases. Each shape is indexed based on a variety of simple and easily computable features which are invariant to articulations, rigid transformations, etc. The features characterize pairwise geometric relationships between interest points on the shape. The fact that each shape is represented using multiple features instead of a single global feature that captures the shape and provides robustness to the approach. Shapes in the database are ordered according to their similarity with the query shape and similar shapes are retrieved using an efficient scheme.

1. H. Ling and D. W. Jacobs, "Shape classification using the inner-distance," IEEE Trans. Pattern Anal. Mach. Intell. , vol. 29, no. 2, pp. 286–299, Feb. 2007.
2. Y. Wang, H. Jiang, M. Drew, L. Ze-Nian, and G. Mori, "Unsupervised discovery of action classes," in Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2006, pp. 1654–1661.
3. A. Thayananthan, B. Stenger, P. H. S. Torr, and R. Cipolla, "Shape context and chamfer matching in cluttered scenes," in Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2003, pp. 127–133.
4. M. Daliri and V. Torre, "Robust symbolic representation for shape recognition and retrieval," Pattern Recognit. , vol. 41, no. 5, pp. 1799–1815, 2008.
5. G. McNeill and S. Vijayakumar, "Hierarchical procrustes matching for shape retrieval," in Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2006, pp. 885–894.
6. A. Peter, A. Rangarajan, and J. Ho, "Shape lne rouge: Sliding wavelets for indexing and retrieval," in Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2008, pp. 1–8.
7. T. Adamek and N. OConnor, "A multiscale representation method for nonrigid shapes with a single closed contour," IEEE Trans. Circuits Syst. Video Technol. , vol. 14, no. 5, pp. 742–753, May 2004.
8. A. B. Hamza and H. Krim, "Geodesic object representation and recognition," in DGCI, LNCS 2886, 2003, pp. 378–387.
9. S. Belongie, J. Malik, and J. Puzicha, "Shape matching and object recognition using shape contexts," IEEE Trans. Pattern Anal. Mach. Intell. , vol. 24, no. 4, pp. 509–522, Apr. 2002.
10. Y. Liu, H. Zha, and H. Qin, "The generalized shape distributions for shape matching and analysis," in Proc. Int. Conf. Shape Modeling and Applications, 2002.
11. P. Tresadern and I. Reid, "An evaluation of shape descriptors for image retrieval in human pose estimation," in Proc. British Machine Vision Conf. , 2007.
12. D. Rafiei and A. Mendelzon, "Efficient retrieval of similar shapes," Int. J. Very Large Data Bases, vol. 11, no. 1, pp. 17–27, 2002.

Fast Retrieval Indexing Shape Matching.