Learning graphs to match

Proceedings of the IEEE International Conference on Computer Vision

Volumn , Issue , 2013, Pages 25-32

  Cho, Minsu ^a,c   Alahari, Karteek ^a,c   Ponce, Jean ^b,c  

^a INRIA   (France)

^b ECOLE NORMALE SUPÉRIEURE   (France)

^c CNRS   (France)

Author keywords

feature correspondence; graph learning; graph matching; object recognition

Indexed keywords

OBJECT RECOGNITION;

EXPERIMENTAL EVALUATION; FEATURE CORRESPONDENCE; GRAPH LEARNING; GRAPH MATCHINGS; GRAPH REPRESENTATION; LEARNING GRAPHS; OBSERVED DATA; VISUAL OBJECTS;

GRAPH THEORY;

EID: 84898824034     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2013.11     Document Type: Conference Paper

References (33)

1. http://www.di.ens.fr/willow/research/graphlearning/.
2. S. Belongie, J. Malik, and J. Puzicha. Shape matching and object recognition using shape contexts. TPAMI, 2002.
3. A. C. Berg, T. L. Berg, and J. Malik. Shape matching and object recognition using low distortion correspondences. In CVPR, 2005.
4. W. Brendel and S. Todorovic. Learning spatiotemporal graphs of human activities. In ICCV, pages 778-785, 2011.
5. T. S. Caetano, J. J. McAuley, L. Cheng, Q. V. Le, and A. J. Smola. Learning graph matching. TPAMI, 2009.
6. M. Cho, J. Lee, and K. M. Lee. Reweighted random walks for graph matching. In ECCV, 2010.
7. M. Cho and K. M. Lee. Progressive graph matching: Making a move of graphs via probabilistic voting. In CVPR, 2012.
8. D. Conte, P. Foggia, C. Sansone, and M. Vento. Thirty years of graph matching in pattern recognition. IJPRAI, 2004.
9. T. Cour, P. Srinivasan, and J. Shi. Balanced graph matching. In NIPS, 2007.
10. N. Dalal and B. Triggs. Histograms of oriented gradients for human detection. In CVPR, 2005.
11. J. Davis and P. Domingos. Bottom-up learning of Markov network structure. In ICML, 2010.
12. O. Duchenne, F. Bach, I. Kweon, and J. Ponce. A tensor-based algorithm for high-order graph matching. In CVPR, 2009.
13. O. Duchenne, A. Joulin, and J. Ponce. A graph-matching kernel for object categorization. In ICCV, 2011.
14. S. Gold and A. Rangarajan. A graduated assignment algorithm for graph matching. Trans. PAMI, 1996.
15. S. Hare, A. Saffari, and P. H. S. Torr. Efficient Online Structured Output Learning for Keypoint-Based Object Tracking. In CVPR, 2012.
16. T. Joachims, T. Finley, and C.-N. Yu. Cutting-plane training of structural svms. Machine Learning, 2009.
17. S.-I. Lee, V. Ganapahthi, and D. Koller. Efficient Structure Learning of Markov Networks using L1-Regularization. In NIPS, 2006.
18. M. Leordeanu and M. Hebert. A spectral technique for correspondence problems using pairwise constraints. In ICCV, 2005.
19. M. Leordeanu, M. Hebert, and R. Sukthankar. Beyond local appearance: Category recognition from pairwise interactions of simple features. In CVPR, 2007.
20. M. Leordeanu, M. Hebert, and R. Sukthankar. An integer projected fixed point method for graph matching and map inference. In NIPS, 2009.
21. M. Leordeanu, R. Sukthankar, and M. Hebert. Unsupervised learning for graph matching. IJCV, 2012.
22. D. G. Lowe. Distinctive image features from scale-invariant keypoints. IJCV, 2004.
23. J. Matas, O. Chum, M. Urban, and T. Pajdla. Robust wide baseline stereo from maximally stable extremal regions. In BMVC, 2002.
24. K. Mikolajczyk and C. Schmid. Scale and affine invariant interest point detectors. IJCV, 2004.
25. S. Nowozin, P. Gehler, and C. Lampert. On parameter learning in CRF-based approaches to object class image segmentation. ECCV, 2010.
26. D. Pachauri, M. Collins, V. SIngh, R. Kondor, and V. S. Deepti Pachauri, Maxwell Collins, Risi Kondor. Incorporating domain knowledge in matching problems via harmonic analysis. In ICML, 2012.
27. A. Sharma, R. Horaud, J. Cech, , and E. Boyer. Topologically-robust 3d shape matching based on diffusion geometry and seed growing. In CVPR, 2011.
28. M. Szummer, P. Kohli, and D. Hoiem. Learning CRFs using graph cuts. In ECCV, 2008.
29. B. Taskar, C. Guestrin, and D. Koller. Max-margin markov networks. In NIPS, 2003.
30. L. Torresani, V. Kolmogorov, and C. Rother. Feature correspondence via graph matching: Models and global optimization. In ECCV, 2008.
31. I. Tsochantaridis, T. Joachims, T. Hofmann, and Y. Altun. Large margin methods for structured and interdependent output variables. JMLR, 2005.
32. S. Umeyama. An eigen decomposition approach to weighted graph matching problems. Trans. PAMI, 1988.
33. B. Yao and L. Fei-Fei. Action recognition with exemplar based 2.5d graph matching. In ECCV, 2012.