A matrix decomposition perspective to multiple graph matching

Proceedings of the IEEE International Conference on Computer Vision

Volumn 2015 International Conference on Computer Vision, ICCV 2015, Issue , 2015, Pages 199-207

  Yan, Junchi ^a,b   Xu, Hongteng ^c,d   Zha, Hongyuan ^c,e   Yang, Xiaokang ^a   Liu, Huanxi ^a   Chu, Stephen ^b  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

^b IBM CHINA RESEARCH LAB   (China)

^c School of Chemistry and Biochemistry   (United States)

^d GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

^e EAST CHINA NORMAL UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER VISION; CONVEX OPTIMIZATION; GRAPHIC METHODS; OPTIMIZATION; PATTERN MATCHING;

CONVEX OPTIMIZATION ALGORITHMS; GRAPH MATCHINGS; MATRIX DECOMPOSITION; NODE MAPPING; STATE OF THE ART; SYNTHETIC DATA; WEIGHTED GRAPH; WIDE SPECTRUM;

IMAGE MATCHING;

EID: 84973890835     PISSN: 15505499     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2015.31     Document Type: Conference Paper

References (66)

1. A. V. Aho, M. Ganapathi, and S. W. Tjiang. Code generation using tree matching and dynamic programming. TOPLAS, 1989.
2. H. A. Almohamad and S. O. Duffuaa. A linear programming approach for the weighted graph matching problem. TPAMI, 1993.
3. S. Boyd, N. Parikh, E. Chu, B. Peleato, and J. Ecjstein. Distributed optimization and statistical learning via the alternating direction method of multipliers. Foundations and Trends in Machine Learning, 2010.
4. T. Caelli and S. Kosinov. An eigenspace projection clustering method for inexact graph matching. TPAMI, 2004.
5. T. Caetano, J. McAuley, L. Cheng, Q. Le, and A. J. Smola. Learning graph matching. TPAMI, 31 (6): 1048-1058, 2009.
6. E. Candes, X. Li, Y. Ma, and J. Wright. Robust principal component analysis Journal of the ACM, 2011.
7. Y. Chen, G. Leonidas, and Q. Huang. Matching partially similar objects via matrix completion. In ICML, 2014.
8. M. Chertok and Y. Keller. Efficient high order matching. TPAMI, 2010.
9. M. Cho, K. Alahari, and J. Ponce. Learning graphs to match. In ICCV, 2013.
10. M. Cho, J. Lee, and K. M. Lee. Reweighted random walks for graph matching. In ECCV, 2010.
11. M. Cho and K. M. Lee. Progressive graph matching: Making a move of graphs via probabilistic voting. In CVPR, 2012.
12. T. Collins, P. Mesejo, and A. Bartoli. An analysis of errors in graph-based keypoint matching and proposed solutions. In ECCV, 2014.
13. D. Conte, P. Foggia, C. Sansone, and M. Vento. Thirty years of graph matching in pattern recognition. IJPRAI, 18 (03): 265-298, 2004.
14. O. Duchenne, F. Bach, I. Kweon, and J. Ponce. A tensor-based algorithm for high-order graph matching. In CVPR, 2009.
15. O. Duchenne, A. Joulin, and J. Ponce. A graph-matching kernel for object categorization. In ICCV, 2011.
16. A. Egozi, Y. Keller, and H. Guterman. A probabilistic approach to spectral graph matching. TPAMI, pages 18-27, 2013.
17. D. Eppstein. Subgraph isomorphism in planar graphs and related problems. In SODA, 1995.
18. M. A. Fischler and R. C. Bolles. Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM, 1981.
19. P. Foggia, G. Percannella, and M. Vento. Graph matching and learning in pattern recognition in the last 10 years. IIPRAI, 2014.
20. T. Funkhouser, M. Kazhdan, P. Shilane, P. Min, W. Kiefer, A. Tal, and D. Dobkin. Modeling by example. TOG, 2004.
21. S. Gold and A. Rangarajan. A graduated assignment algorithm for graph matching. TPAMI, 1996.
22. S. Gold and A. Rangarajan. Softmax to softassign: neural network algorithms for combinatorial opti-mization. J. Artif. Neural Netw, 1996.
23. Q. Huang, G. Zhang, L. Gao, S. Hu, A. Butscher, and L. Guibas. An optimization approach for extracting and encoding consistent maps in a shape collection. ACM Transactions on Graphics (TOG), 2012.
24. K. Jia, T. H. Chan, Z. Zeng, G. Wang, T. Zhang, and Y. Ma. Roml: A robust feature correspondence approach for matching objects in a set of images. ArXiv: 1403. 7877, 2014.
25. T. C. Koopmans and M. Beckmann. Assignment problems and the location of economic activities. Econometrica, pages 53-76, 1957.
26. E. Lawler. The quadratic assignment problem. Management Science, 1963.
27. J. Lee, M. Cho, and K. M. Lee. Hyper-graph matching via reweighted randomwalks. In CVPR, 2011.
28. M. Leordeanu and M. Hebert. A spectral technique for correspondence problems using pairwise constraints. In ICCV, 2005.
29. M. Leordeanu, M. Hebert, and R. Sukthankar. An integer projected fixed point method for graph matching and map inference. In NIPS, 2009.
30. M. Leordeanu, R. Sukthankar, and M. Hebert. Unsupervised learning for graph matching. Int. J. Comput. Vis., pages 28-45, 2012.
31. M. Leordeanu, A. Zanfir, and C. Sminchisescu. Semi-supervised learning and optimization for hypergraph matching. In ICCV, 2011.
32. Y. Li, Z. Y. Yan, J., and J. Yang. Optimum subspace learning and error correction for tensors. In ECCV, 2010.
33. Z. Lin, M. Chen, and Y. Ma. The augmented lagrange multiplier method for exact recovery of corrupted low-rank matrices. ArXiv preprint arXiv: 1009. 5055, 2010.
34. G. Liu, Z. Lin, S. Yan, J. Sun, Y. Yong, and Y. Ma. Robust recovery of subspace structures by low-rank representation. TPAMI, 2013.
35. J. Liu, S. Ji, and J. Ye. Slep: Sparse learning with efficient projections. Arizona State University, 6, 2009.
36. L. Liu, W. Lin, and Y. Zhong. Traffic flow matching with clique and triplet cues. In IEEE International Workshop on Multimedia Signal Processing, 2015.
37. S. Liu, X. Wang, J. Chen, and et al. Topicpanorama: A full picture of relevant topics. VCG, 2014.
38. Z. Liu, H. Qiao, and L. Xu. An extended path following algorithm for graphmatching problem. TPAMI, pages 1451-1456, 2012.
39. E. M. Luks. Isomorphism of graphs of bounded valence can be tested in polynomial time. Journal of Computer and System Sciences, 25 (1), 1982.
40. Y. Mi, L. Liu, W. Lin, and W. Wangg. Extracting recurrent motion flows from crowded scene videos: A coherent motion-based approach. In Intl. Conf. Multimedia Big Data workshop, 2015.
41. D. Pachauri, R. Kondor, and S. Vikas. Solving the multi-way matching problem by permutation synchronization. In NIPS, 2013.
42. G. A. Peng, Y. G. Rasl: Robust alignment by sparse and low-rank decomposition for linearly correlated images. In CVPR, 2010.
43. G. Scott and H. Longuet-Higgins. An algorithm for associating the features of two images. Biological Sciences, pages 21-26, 1991.
44. L. S. Shapiro and M. Brady. Feature-based correspondence: An eigenvector approach. Image Vision Comput., pages 283-288, 1992.
45. Y. Shen, W. Lin, J. Yan, M. Xu, J. Wu, and J. Wang. Person re-identification with correspondence structure learning. In ICCV, 2015.
46. A. Solé-Ribalta and F. Serratosa. Models and algorithms for computing the common labelling of a set of attributed graphs. CVIU, 2011.
47. A. Sole-Ribalta and F. Serratosa. Graduated assignment algorithm for multiple graph matching based on a common labeling. IJPRAI, 2013.
48. P. S. T. Cour and J. Shi. Balanced graph matching. In NIPS, 2006.
49. Y. Tian, J. Yan, H. Zhang, Y. Zhang, X. Yang, and H. Zha. On the convergence of graph matching: Graduated assignment revisited. In ECCV, 2012.
50. S. Umeyama. An eigendecomposition approach to weighted graph matching problems. TPAMI, 1988.
51. F. Viksten, P. Forssén, B. Johansson, and A. Moe. Comparison of local image descriptors for full 6 degree-of-freedom pose estimation. In ICRA, 2009.
52. M. L. Williams, R. C. Wilson, and E. Hancock. Multiple graph matching with Bayesian inference. Pattern Recognition Letters, pages 1275-1281, 1997.
53. J. Xiao, H. Cheng, H. Sawhney, and F. Han. Vehicle detection and tracking in wide field-of-view aerial video. In CVPR, 2010.
54. J. Yan, M. Cho, H. Zha, X. Yang, and S. Chu. Multi-graph matching via affinity optimization with graduated consistency regularization. TPAMI, 2016.
55. J. Yan, Y. Li, W. Liu, H. Zha, X. Yang, and S. Chu. Graduated consistencyregularized optimization for multi-graph matching. In ECCV, 2014.
56. J. Yan, Y. Tian, H. Zha, X. Yang, Y. Zhang, and S. Chu. Joint optimization for consistent multiple graph matching. In ICCV, 2013.
57. J. Yan, J. Wang, H. Zha, and X. Yang. Consistency-driven alternating optimization for multigraph matching: A unified approach. TIP, 2015.
58. J. Yan, J. Wang, H. Zha, X. Yang, and S. M. Chu. Multi-view point registration via alternating optimization. In AAAI, 2015.
59. J. Yan, C. Zhang, H. Zha, W. Liu, X. Yang, and S. M. Chu. Discrete hypergraph matching. In CVPR, 2015.
60. J. Yan, M. Zhu, H. Liu, and Y. Liu. Visual saliency detection via sparsity pursuit. Signal Processing Letters, IEEE, 2010.
61. M. Zaslavskiy, F. R. Bach, and J.-P. Vert. A path following algorithm for the graph matching problem. TPAMI, 2009.
62. Z. Zeng, T. H. Chan, K. Jia, and D. Xu. Finding correspondence from multiple images via sparse and low-rank decomposition. In ECCV, 2012.
63. Z. Zeng, S. Xiao, K. Jia, T. Chan, S. Gao, D. Xu, and Y. Ma. Learning by associating ambiguously labeled images. In CVPR, 2013.
64. Z. Zhang. Iterative point matching for registration of free-form curves and surfaces. IJCV, 1994.
65. F. Zhou and F. D. Torre. Factorized graph matching. In CVPR, 2012.
66. X. Zhou and M. Z. Amd Kostas Daniilidis. Multi-image matching via fast alternating minimization. In arXiv: 1505. 04845v1, 2015.