Balancing deformability and discriminability for shape matching

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6313 LNCS, Issue PART 3, 2010, Pages 411-424

  Ling, Haibin ^a   Yang, Xingwei ^a   Latecki, Longin Jan ^a  

^a Temple University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; EMBEDDINGS;

CONTEXT INFORMATION; CONTEXT SENSITIVE; DISCRIMINABILITY; HIGHER-DIMENSIONAL; IMAGE REPRESENTATIONS; SHAPE COMPARISON; SHAPE RETRIEVAL; STATE OF THE ART;

DEFORMATION;

EID: 78149323821     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15558-1_30     Document Type: Conference Paper

References (42)

1. Adamek, T., O'Connor, N.: A multiscale representation method for nonrigid shapes with a single closed contour. IEEE Tran. Cir. & Sys. for Video Technology 14(5), 742-753 (2004)
2. Alajlan, N., Kamel, M., Freeman, G.: Geometry-based image retrieval in binary image databases. IEEE Trans. Pattern Anal. Mach. Intell. 30(6), 1003-1013 (2008)
3. Aslan, C., Erdem, A., Erdem, E., Tari, S.: Disconnected skeleton: Shape at its absolute scale. IEEE Trans. Pattern Anal. Mach. Intell. 30(12), 2188-2203 (2008)
4. Baseski, E., Erdem, A., Tari, S.: Dissimilarity between two skeletal trees in a context. Pattern Recognition 42(3), 370-385 (2009)
5. Belongie, S., Malik, J., Puzicha, J.: Shape matching and object recognition using shape contexts. IEEE Trans. Pattern Anal. Mach. Intell. 24(4), 509-522 (2002)
6. Bronstein, A.M., Bronstein, M.M., Kimmel, R.: Generalized multidimensional scaling: a framework for isometry-invariant partial surface matching. Proc. Nat. Acad. Sci. 103(5), 1168-1172 (2006)
7. Bronstein, A.M., Bronstein, M.M., Bruckstein, A.M., Kimmel, R.: Analysis of two-dimensional non-rigid shapes. Int. Journal of Computer Vision 78(1), 67-88 (2008)
8. Bronstein, A.M., Bronstein, M.M., Kimmel, R.: A Gromov-Hausdorff framework with diffusion geometry for topologically-robust non-rigid shape matching. Int. Journal of Computer Vision 89(2-3), 266-286 (2010)
9. Cheng, H., Liu, Z., Zheng, N., Yang, J.: A deformable local image descriptor. In: CVPR, pp. 1-8 (2008)
10. Elad, A., Kimmel, R.: On bending invariant signatures for surfaces. IEEE Trans. Pattern Anal. Mach. Intell. 25(10), 1285-1295 (2003)
11. Felzenszwalb, P., Schwartz, J.: Hierarchical matching of deformable shapes. In: CVPR, pp. 1-8 (2007)
12. Hu, M.: Visual pattern recognition by moment invariants. IRE Tran. Information Theory 8, 179-187 (1962)
13. Johnson, A.E., Hebert, M.: Using spin images for efficient object recognition in cluttered 3D scenes. IEEE Trans. Pattern Anal. Mach. Intell. 21(5), 433-449 (1999)
14. Kadir, T., Zisserman, A., Brady, M.: An affine invariant salient region detector. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3021, pp. 228-241. Springer, Heidelberg (2004)
15. Kontschieder, P., Donoser, M., Bischof, H.: Beyond pairwise shape similarity analysis. In: Zha, H., Taniguchi, R.-i., Maybank, S. (eds.) Computer Vision - ACCV 2009. LNCS, vol. 5996, pp. 655-666. Springer, Heidelberg (2009)
16. Latecki, L.J., Lakämper, R.: Shape similarity measure based on correspondence of visual parts. IEEE Trans. Pattern Anal. Mach. Intell. 22(10), 1185-1190 (2000)
17. Latecki, L.J., Lakamper, R., Eckhardt, U.: Shape descriptors for non-rigid shapes with a single closed contour. In: CVPR, vol. 1, pp. 424-429 (2000)
18. Lazebnik, S., Schmid, C., Ponce, J.: A sparse texture representation using affine-invariant regions. IEEE Trans. Pattern Anal. Mach. Intell. 27(8), 1265-1278 (2005)
19. Lin, L., Zeng, K., Liu, X.B., Zhu, S.C.: Layered Graph Matching by Composite Cluster Sampling with Collaborative and Competitive Interactions. In: CVPR (2009)
20. Lindeberg, T.: Feature detection with automatic scale selection. Int. Journal of Computer Vision 30(2), 79-116 (1998)
21. Ling, H., Jacobs, D.W.: Deformation invariant image matching. In: ICCV, pp. 1466-1473 (2005)
22. H. Ling and D.W. Jacobs. Shape classification using the inner-distance. IEEE Trans. Pattern Anal. Mach. Intell., 29(2):286-299, 2007.
23. Ling, H., Okada, K.: EMD-L1: An Efficient and Robust Algorithm for Comparing Histogram-Based Descriptors. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3953, pp. 330-343. Springer, Heidelberg (2006) (Pubitemid 44029688)
24. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. Journal of Computer Vision 60(2), 91-110 (2004)
25. Matas, J., Chum, O., Urban, M., Pajdla, T.: Robust wide baseline stereo from maximally stable extremal regions. In: BMVC (2002)
26. McNeill, G., Vijayakumar, S.: Hierarchical procrustes matching for shape retrieval. In: CVPR, pp. 885-894 (2006)
27. Mikolajczyk, K., Schmid, C.: Scale & affine invariant interest point detectors. Int. Journal of Computer Vision 60(1), 63-86 (2004)
28. Mokhtarian, F., Abbasi, S., Kittler, J.: Efficient and robust retrieval by shape content through curvature scale space. In: Wkshp on Image DataBases and MultiMedia Search (1996)
29. Rudin, L., Osher, S., Fatemi, E.: Nonlinear total variation based noise removal algorithms. Physica D 60(1-4), 259-268 (1992)
30. Rustamov, R., Lipman, Y., Funkhouser, T.: Interior Distance Using Barycentric Coordinates. In: Symposium on Geometry Processing (2009)
31. Sebastian, T.B., Klein, P.N., Kimia, B.B.: Recognition of shapes by editing their shock graphs. IEEE Trans. Pattern Anal. Mach. Intell. 26(5), 550-571 (2004)
32. Sethian, J.A.: A fast marching level set method for monotonically advancing fronts. Proc. Nat. Acad. Sci. 93(4), 1591-1595 (1996)
33. Sivic, J., Zisserman, A.: Video Google: Efficient visual search of videos. In: Ponce, J., Hebert, M., Schmid, C., Zisserman, A. (eds.) Toward Category-Level Object Recognition, pp. 127-144 (2006)
34. Sochen, N., Kimmel, R., Malladi, R.: A general framework for low level vision. IEEE Trans. Image Processing 7(3), 310-318 (1998) (Pubitemid 128745349)
35. Thompson, D.W.: On Growth and Form. Cambridge University Press, Cambridge (1917)
36. Torralba, A., Murphy, K., Freeman, W., Rubin, M.: Context-based vision system for place and object recognition. In: ICCV, pp. 273-280 (2003)
37. Vedaldi, A., Soatto, S.: Features for recognition: Viewpoint invariance for non-planar scenes. In: ICCV, vol. 2, pp. 1474-1481 (2005)
38. Xu, C., Liu, J., Tang, X.: 2d shape matching by contour flexibility. IEEE Trans. Pattern Anal. Mach. Intell. 31(1), 180-186 (2009)
39. Xu, Y., Ji, H., Fermüller, C.: A projective invariant for textures. In: CVPR, pp. 1932-1939 (2006)
40. Yang, X., Bai, X., Latecki, L.J., Tu, Z.: Improving shape retrieval by learning graph transduction. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part IV. LNCS, vol. 5305, pp. 788-801. Springer, Heidelberg (2008)
41. Yang, X., Köknar-Tezel, S., Latecki, L.J.: Locally constrained diffusion process on locally densified distance spaces with applications to shape retrieval. In: CVPR (2009)
42. Zhang, J., Marszalek, M., Lazebnik, S., Schmid, C.: Local features and kernels for classification of texture and object categories: A comprehensive study. Int. Journal of Computer Vision 73(2), 213-238 (2007) (Pubitemid 46181625)