Shape recognition based on Kernel-edit distance

Computer Vision and Image Understanding

Volumn 114, Issue 10, 2010, Pages 1097-1103

  Daliri, Mohammad Reza ^a,b   Torre, Vincent ^c  

^a IRAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Iran)

^b INSTITUTE FOR RESEARCH IN FUNDAMENTAL SCIENCES IPM   (Iran)

^c SISSA   (Italy)

Author keywords

Dynamic programming; Kernel methods; Kernel edit distance; Shape contexts; Shape recognition; Symbolic representation

Indexed keywords

EDIT DISTANCE; KERNEL METHODS; SHAPE CONTEXTS; SHAPE RECOGNITION; SYMBOLIC REPRESENTATION;

DYNAMIC PROGRAMMING;

EID: 77956177807     PISSN: 10773142     EISSN: 1090235X     Source Type: Journal    
DOI: 10.1016/j.cviu.2010.07.002     Document Type: Article

References (39)

1. M.R. Daliri, and V. Torre Robust symbolic representation for shape recognition and retrieval Pattern Recogn. 41 5 2008 1799 1815
2. H. Freeman Computer processing of line-drawing images Comput. Surv. 6 1 1974 57 97
3. C.H. Wu, and S.J. Horng Run-length chain coding and scalable computation of a shape's moments using reconfigurable optical buses IEEE Trans. Syst. Man Cybern., Part B 34 2 2004 845 855
4. S. Belongie, J. Malik, and J. Puzicha Shape matching and object recognition using shape contexts IEEE Trans. PAMI 24 24 2002 509 521
5. H. Blum, A transformation for extracting new descriptors of shape, in: W. Walthen-Dunn (Ed.), Models for the Perception of Speech and Visual Form, MIT Press, 1967, pp. 362-379.
6. T.B. Sebastian, P.N. Klein, and B.B. Kimia Recognition of shapes by editing their shock graphs IEEE Trans. PAMI 26 5 2004 550 571
7. J.J. Zou, and H. Yan Skeletonization of Ribbon-like shapes based on regularity and singularity analyses IEEE Trans. Syst. Man Cybern., Part B 31 3 2001 401 407
8. A. Bonnassie, F. Peyrin, and D. Attali A new method for analyzing local shape in three-dimensional images based on medial axis transformation IEEE Trans. Syst. Man Cybern., Part B 33 4 2003 700 705
9. E. Attalla, and P. Siy Robust shape similarity retrieval based on contour segmentation polygonal multiresolution and elastic matching Pattern Recogn. 38 12 2005 2229 2241
10. H. Ling, and D.W. Jacobs Shape classification using the inner-distance IEEE Trans. PAMI 29 2 2007 286 299
11. X. Yang, X. Bai, L.J. Latecki, Z. Tu, Improving shape retrieval by learning graph transduction, in: Proc. European Conf. on Computer Vision (ECCV), 2008.
12. X. Yang, S. Koknar-Tezel, L.J. Latecki, Locally constrained diffusion process on locally densified distance spaces with applications to shape retrieval, in: Proc. Computer Vision and Pattern Recognition (CVPR), 2009, pp. 357-364.
13. E.G.M. Petrakis, A. Diplaros, and E. Milios Matching and retrieval of distorted and occluded shapes using dynamic programming IEEE Trans. PAMI 24 11 2002 1501 1516
14. T.F. Cootes, C.J. Taylor, D.H. Cooper, and J. Graham Active shape models - their training and application Comput. Vision Image Understand. 61 1 1995 38 59
15. E.S. Ristad, and P.N. Yianilos Learning string-edit distance IEEE Trans. PAMI 20 5 1998 522 532
16. V. Vapnik The Nature of Statistical Learning Theory 1995 Springer-Verlag
17. B. Scholkopf, A. Smola, and K.R. Muller Nonlinear component analysis as a kernel eigenvalue problem Neural Comput. 10 1998 1299 1319
18. S.J. Kim, A. Magnani, S. Boyd, Optimal kernel selection in kernel fisher discriminant analysis, in: Proc. of the 23rd Int. Conf. on Machine Learning (ICML 2006), 2006, pp. 465-472.
19. C. Cortes, P. Haffner, M. Mohri, Positive definite rational kernels, in: Proc. of the 16th Annual Conf. on Computational Learning Theory (COLT2003), Lecture Notes in Computer Science, vol. 2777, Springer, Heidelberg, Germany, 2003, pp. 41-56.
20. B. Scholkpf, C.J.C. Burges, and A.J. Smola Advances in Kernel Methods: Support Vector Learning 1998 The MIT Press
21. J. Zhang, M. Marszalek, S. Lazebnik, and C. Schmid Local features and kernels for classification of texture and object categories: a comprehensive study Int. J. Comput. Vision 73 2 2007 213 238
22. N. Cristianini, and J. Shawe-Taylor An Introduction to Support Vector Machines 2000 Cambridge University Press
23. C.W. Hsu, and C.J. Lin A comparison of methods for multiclass support vector machines IEEE Trans. Neural Networks 13 2 2002 415 425
24. R. Rifkin, and A. Klautau In defense of one-vs-all classification J. Mach. Learn. Res. 5 2004 101 141
25. A. Ghosh, and N. Petkov Robustness of shape descriptors to incomplete contour representations IEEE Trans. Pattern Anal. Mach. Intell. 27 11 2005 1793 1804
26. M. Neuhaus, and H. Bunke Edit distance-based kernel functions for structural pattern classification Pattern Recogn. 39 2006 1852 1863
27. A.M. Martinez, and A.C. Kak PCA versus LDA IEEE Trans. PAMI 23 2 2004 228 233
28. L. Gorelick, M. Galun, E. Sharon, R. Basri, and A. Brandt Shape representation and classification using the poisson equation IEEE Trans. PAMI 28 12 2006 1991 2005
29. T.B. Sebastian, P.N. Klein, and B.B. Kimia Shock-based indexing into large shape databases Proc. Eur. Conf. Comput. Vision 3 2002 731 746
30. E.G.M. Petrakis, A. Diplaros, and E. Milios Matching and retrieval of distorted and occluded shapes using dynamic programming IEEE Trans. PAMI 24 11 2002 1501 1516
31. F. Mokhtarian, and M. Bober Curvature Scale Space Representation: Theory, Applications & MPEG-7 Standardization 2003 Kluwer Academic Publishers Dordrecht
32. L. Latecki, R. Lakamper, U. Eckhardt, Shape descriptors for non-rigid shapes with a single closed contour, in: Proc. of the IEEE Conf. on CVPR, 2000, pp. 424-429.
33. B.J. Super, Learning chance probability functions for shape retrieval or classification, in: Proc. of the IEEE Workshop on Learning in Computer Vision and Pattern Recognition, June 2004.
34. B.J. Super, Improving object recognition accuracy and speed through non-uniform sampling, in: Proc. SPIE Conference Intelligent Robots and Computer Vision XXI: Algorithms, Techniques, and Active Vision, Providence, RI, SPIE, vol. 5267, 2003, pp. 228-239.
35. B.J. Super Retrieval from shape databases using chance probability functions and fixed correspondence Int. J. Pattern Recogn. Artif. Intell. 20 8 2006 1117 1137
36. K.B. Sun, and B.J. Super Classification of contour shapes using class segment sets Proc. Comput. Vision Pattern Recogn. (CVPR) 2 2005 727 733
37. M.R. Daliri, E. Delponte, A. Verri, and V. Torre Shape categorization using string kernels, SSPR/SPR Lect. Notes Comput. Sci. (LNCS) 4109 2006 297 305
38. M.R. Daliri, V. Torre, Shape recognition and retrieval using string of symbols, in: Proceedings of the Fifth International Conference on Machine Learning and Application (ICMLA06), 2006, pp. 101-108.
39. B. Leibe, B. Schiele, Analyzing appearance and contour based methods for object categorization, in: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), vol. 2, 2003, pp. 409-415.