Density Maximization for Improving Graph Matching With Its Applications

IEEE Transactions on Image Processing

Volumn 24, Issue 7, 2015, Pages 2110-2123

  Wang, Chao ^a   Wang, Lei ^a   Liu, Lingqiao ^b  

^a UNIVERSITY OF WOLLONGONG   (Australia)

^b UNIVERSITY OF ADELAIDE   (Australia)

Author keywords

Dense Correspondence; Graph Matching; Image Enhancement; Image retrieval; Mask Transfer; Sparse Feature Matching

Indexed keywords

COMPUTER VISION; IMAGE ENHANCEMENT; IMAGE PROCESSING; IMAGE RETRIEVAL; STATISTICS;

DENSE CORRESPONDENCES; EXPERIMENTAL EVALUATION; GRAPH MATCHINGS; IMAGE PROCESSING AND COMPUTER VISION; OBJECTIVE FUNCTIONS; OUTLIER ELIMINATION; SPARSE FEATURES; STATE-OF-THE-ART METHODS;

IMAGE MATCHING;

EID: 84927723745     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2015.2416639     Document Type: Article

References (60)

1. D. Conte, P. Foggia, C. Sansone, and M. Vento, "Thirty years of graph matching in pattern recognition," Int. J. Pattern Recognit. Artif. Intell., vol. 18, no. 3, pp. 265-298, 2004.
2. A. C. Berg, T. L. Berg, and J. Malik, "Shape matching and object recognition using low distortion correspondences," in Proc. IEEE CVPR, Jun. 2005, pp. 26-33.
3. A. Bartoli, M. Perriollat, and S. Chambon, "Generalized thin-plate spline warps," Int. J. Comput. Vis., vol. 88, no. 1, pp. 85-110, 2010.
4. O. Chum and J. Matas, "Matching with PROSAC-Progressive sample consensus," in Proc. IEEE CVPR, Jun. 2005, pp. 220-226.
5. M. Cho, J. Lee, and K. M. Lee, "Reweighted random walks for graph matching," in Proc. ECCV, 2010, pp. 492-505.
6. T. Cour, P. Srinivasan, and J. Shi, "Balanced graph matching," in Advances in Neural Information Processing Systems. Cambridge, MA, USA: MIT Press, 2007.
7. M. Leordeanu and M. Hebert, "A spectral technique for correspondence problems using pairwise constraints," in Proc. 10th IEEE ICCV, Oct. 2005, pp. 1482-1489.
8. M. Leordeanu, M. Herbert, and R. Sukthankar, "An integer projected fixed point method for graph matching and MAP inference," in Advances in Neural Information Processing Systems. Red Hook, NY, USA: Curran & Associates Inc., 2009.
9. L. Torresani, V. Kolmogorov, and C. Rother, "Feature correspondence via graph matching: Models and global optimization," in Proc. 10th ECCV, 2008, pp. 596-609.
10. J. Maciel and J. P. Costeira, "A global solution to sparse correspondence problems," IEEE Trans. Pattern Anal. Mach. Intell., vol. 25, no. 2, pp. 187-199, Feb. 2003.
11. M. Gori, M. Maggini, and L. Sarti, "Exact and approximate graph matching using random walks," IEEE Trans. Pattern Anal. Mach. Intell., vol. 27, no. 7, pp. 1100-1111, Jul. 2005.
12. Y. Tian, J. Yan, H. Zhang, Y. Zhang, X. Yang, and H. Zha, "On the convergence of graph matching: Graduated assignment revisited," in Proc. 12th ECCV, 2012, pp. 821-835.
13. M. Cho and K. M. Lee, "Progressive graph matching: Making a move of graphs via probabilistic voting," in Proc. IEEE CVPR, Jun. 2012, pp. 398-405.
14. D. G. Lowe, "Object recognition from local scale-invariant features," in Proc. 7th IEEE ICCV, Sep. 1999, pp. 1150-1157.
15. O. Duchenne, F. Bach, I. Kweon, and J. Ponce, "A tensor-based algorithm for high-order graph matching," in Proc. IEEE CVPR, Jun. 2009, pp. 1980-1987.
16. J. Lee, M. Cho, and K. M. Lee, "Hyper-graph matching via reweighted random walks," in Proc. IEEE CVPR, Jun. 2011, pp. 1633-1640.
17. R. Zass and A. Shashua, "Probabilistic graph and hypergraph matching,"in Proc. IEEE CVPR, Jun. 2008, pp. 1-8.
18. F. Zhou and F. de la Torre, "Deformable graph matching," in Proc. IEEE CVPR, Jun. 2013, pp. 2922-2929.
19. H. Li, E. Kim, X. Huang, and L. He, "Object matching with a locally affine-invariant constraint," in Proc. IEEE CVPR, Jun. 2010, pp. 1641-1648.
20. M. Cho, J. Sun, O. Duchenne, and J. Ponce, "Finding matches in a haystack: A max-pooling strategy for graph matching in the presence of outliers," in Proc. IEEE CVPR, Jun. 2014, pp. 2091-2098.
21. M. Cho, J. Lee, and K. M. Lee, "Feature correspondence and deformable object matching via agglomerative correspondence clustering," in Proc. IEEE 12th ICCV, Sep./Oct. 2009, pp. 1280-1287.
22. M. Cho and K. M. Lee, "Authority-shift clustering: Hierarchical clustering by authority seeking on graphs," in Proc. IEEE CVPR, Jun. 2010, pp. 3193-3200.
23. W. Zhang, X. Wang, D. Zhao, and X. Tang, "Graph degree linkage: Agglomerative clustering on a directed graph," in Proc. 12th ECCV, 2012, pp. 428-441.
24. H. Liu, L. J. Latecki, and S. Yan, "Fast detection of dense subgraphs with iterative shrinking and expansion," IEEE Trans. Pattern Anal. Mach. Intell., vol. 35, no. 9, pp. 2131-2142, Sep. 2013.
25. S. Jouili, S. Tabbone, and V. Lacroix, "Median graph shift: A new clustering algorithm for graph domain," in Proc. 20th ICPR, 2010, pp. 950-953.
26. W.-Y. Lin, S. Liu, Y. Matsushita, T.-T. Ng, and L.-F. Cheong, "Smoothly varying affine stitching," in Proc. IEEE CVPR, Jun. 2011, pp. 345-352.
27. R. Szeliski, "Image alignment and stitching: A tutorial," Found. Trends Comput. Graph. Comput. Vis., vol. 2, no. 1, pp. 1-104, 2006.
28. D. Scharstein and R. Szeliski, "A taxonomy and evaluation of dense two-frame stereo correspondence algorithms," Int. J. Comput. Vis., vol. 47, nos. 1-3, pp. 7-42, 2002.
29. A. Bruhn, J. Weickert, and C. Schnorr, "Lucas/Kanade meets Horn/Schunck: Combining local and global optic flow methods," Int. J. Comput. Vis., vol. 61, no. 3, pp. 211-231, 2005.
30. P. Weinzaepfel, J. Revaud, Z. Harchaoui, and C. Schmid, "DeepFlow: Large displacement optical flow with deep matching,"in Proc. IEEE ICCV, Dec. 2013, pp. 1385-1392.
31. M. Leordeanu, A. Zanfir, and C. Sminchisescu, "Locally affine sparse-to- dense matching for motion and occlusion estimation," in Proc. IEEE ICCV, Dec. 2013, pp. 1721-1728.
32. J. Kim, C. Liu, F. Sha, and K. Grauman, "Deformable spatial pyramid matching for fast dense correspondences," in Proc. IEEE CVPR, Jun. 2013, pp. 2307-2314.
33. C. Barnes, E. Shechtman, D. B. Goldman, and A. Finkelstein, "The generalized patchmatch correspondence algorithm," in Proc. ECCV, 2010, pp. 29-43.
34. Y. HaCohen, E. Shechtman, D. B. Goldman, and D. Lischinski, "Non-rigid dense correspondence with applications for image enhancement," in Proc. SIGGRAPH, 2011, Art. ID 70.
35. C. Liu, J. Yuen, and A. Torralba, "SIFT flow: Dense correspondence across scenes and its applications," IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 5, pp. 978-994, May 2011.
36. J. Matas, O. Chum, M. Urban, and T. Pajdla, "Robust wide baseline stereo from maximally stable extremal regions," in Proc. BMVC, 2002, pp. 1-10.
37. K. Mikolajczyk and C. Schmid, "Scale & affine invariant interest point detectors," Int. J. Comput. Vis., vol. 60, no. 1, pp. 63-86, 2004.
38. C. Wang, L. Wang, and L. Liu, "Improving graph matching via density maximization," in Proc. IEEE ICCV, Dec. 2013, pp. 3424-3431.
39. M. Cho and K. M. Lee, "Mode-seeking on graphs via random walks,"in Proc. IEEE CVPR, Jun. 2012, pp. 606-613.
40. Y. A. Sheikh, E. A. Khan, and T. Kanade, "Mode-seeking by medoid-shifts,"in Proc. IEEE 11th ICCV, Oct. 2007, pp. 1-8.
41. V. Ferrari, T. Tuytelaars, and L. Van Gool, "Simultaneous object recognition and segmentation from single or multiple model views,"Int. J. Comput. Vis., vol. 67, no. 2, pp. 159-188, 2006.
42. M. Cho, Y. M. Shin, and K. M. Lee, "Co-recognition of image pairs by data-driven Monte Carlo image exploration," in Proc. 10th ECCV, 2008, pp. 144-157.
43. A. Myronenko and X. Song, "Point set registration: Coherent point drift,"IEEE Trans. Pattern Anal. Mach. Intell., vol. 32, no. 12, pp. 2262-2275, Dec. 2010.
44. W.-Y. Lin, L. Liu, Y. Matsushita, K.-L. Low, and S. Liu, "Aligning images in the wild," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), Jun. 2012, pp. 1-8.
45. E. Trulls, I. Kokkinos, A. Sanfeliu, and F. Moreno-Noguer, "Dense segmentation-aware descriptors," in Proc. IEEE CVPR, Jun. 2013, pp. 2890-2897.
46. H. Yang, W.-Y. Lin, and J. Lu, "DAISY filter flow: A generalized discrete approach to dense correspondences," in Proc. IEEE CVPR, Jun. 2014, pp. 3406-3413.
47. Y. Y. Boykov and M.-P. Jolly, "Interactive graph cuts for optimal boundary & region segmentation of objects in N-D images," in Proc. 8th IEEE CVPR, Dec. 2001, pp. 105-112.
48. C. Rother, V. Kolmogorov, and A. Blake, "'GrabCut': Interactive fore-ground extraction using iterated graph cuts," in Proc. SIGGRAPH, 2004, pp. 309-314.
49. M. Rubinstein, A. Joulin, J. Kopf, and C. Liu, "Unsupervised joint object discovery and segmentation in Internet images," in Proc. IEEE CVPR, Jun. 2013, pp. 1939-1946.
50. Y. Boykov and V. Kolmogorov, "An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision,"IEEE Trans. Pattern Anal. Mach. Intell., vol. 26, no. 9, pp. 1124-1137, Sep. 2004.
51. A. Joulin, F. Bach, and J. Ponce, "Discriminative clustering for image co-segmentation," in Proc. IEEE CVPR, Jun. 2010, pp. 1943-1950.
52. J. Zhu, S. C. H. Hoi, M. R. Lyu, and S. Yan, "Near-duplicate keyframe retrieval by nonrigid image matching," in Proc. 16th ACM Multimedia, 2008, pp. 41-50.
53. J. Philbin, O. Chum, M. Isard, J. Sivic, and A. Zisserman, "Object retrieval with large vocabularies and fast spatial matching," in Proc. IEEE CVPR, Jun. 2007, pp. 1-8.
54. D. Nister and H. Stewenius, "Scalable recognition with a vocabulary tree," in Proc. IEEE CVPR, Jun. 2006, pp. 2161-2168.
55. H. Jegou, M. Douze, C. Schmid, and P. Perez, "Aggregating local descriptors into a compact image representation," in Proc. IEEE CVPR, Jun. 2010, pp. 3304-3311.
56. L. Fei-Fei, R. Fergus, and P. Perona, "One-shot learning of object categories," IEEE Trans. Pattern Anal. Mach. Intell., vol. 28, no. 4, pp. 594-611, Apr. 2006.
57. J.-M. Morel and G. Yu, "ASIFT: A new framework for fully affine invariant image comparison," SIAM J. Imag. Sci., vol. 2, no. 2, pp. 438-469, 2009.
58. F. Pitie, A. C. Kokaram, and R. Dahyot, "Automated colour grading using colour distribution transfer," Comput. Vis. Image Understand., vol. 107, nos. 1-2, pp. 123-137, 2007.
59. X. An and F. Pellacini, "User-controllable color transfer," Comput. Graph. Forum, vol. 29, no. 2, pp. 263-271, 2010.
60. K. Mikolajczyk et al., "A comparison of affine region detectors,"Int. J. Comput. Vis., vol. 65, nos. 1-2, pp. 43-72, 2005.