Exhaustive and efficient constraint propagation: A graph-based learning approach and its applications

International Journal of Computer Vision

Volumn 103, Issue 3, 2013, Pages 306-325

  Lu, Zhiwu ^a   Peng, Yuxin ^a  

^a PEKING UNIVERSITY   (China)

Author keywords

Constrained spectral clustering; Cross modal retrieval; Multi source data; Pairwise constraint propagation; Semi supervised classification

Indexed keywords

CONSTRAINED SPECTRAL CLUSTERING; CROSS-MODAL; MULTISOURCE DATA; PAIRWISE CONSTRAINTS; SEMI-SUPERVISED CLASSIFICATION;

SUPERVISED LEARNING;

DISTRIBUTED COMPUTER SYSTEMS;

EID: 84878727865     PISSN: 09205691     EISSN: 15731405     Source Type: Journal    
DOI: 10.1007/s11263-012-0602-z     Document Type: Article

References (45)

1. Bartels, R.; Stewart, G. (1972). Solution of the matrix equation AX+XB=C. Communications of the ACM, 15(9), 820-826.
2. Basu, S.; Bilenko, M.; Mooney, R. (2004). A probabilistic framework for semi-supervised clustering. In Proceedings of the SIGKDD (pp. 59-68).
3. Bekkerman, R.; Jeon, J. (2007). Multi-modal clustering for multimedia collections. In Proceedings of the CVPR (pp. 1-8).
4. Blei, D.; Ng, A.; Jordan, M. (2003). Latent Dirichlet allocation. Journal of Machine Learning Research, 3, 993-1022.
5. Bruno, E.; Moenne-Loccoz, N.; Marchand-Maillet, S. (2008). Design of multimodal dissimilarity spaces for retrieval of video documents. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(9), 1520-1533.
6. Carson, C.; Belongie, S.; Greenspan, H.; Malik, J. (2002). Blobworld: Image segmentation using expectation-maximization and its application to image querying. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(8), 1026-1038.
7. Chen, G.; Lerman, G. (2009). Spectral curvature clustering (scc). International Journal of Computer Vision, 81, 317-330.
8. Eaton, E.; desJardins, M.; Jacob, S. (2010). Multi-view clustering with constraint propagation for learning with an incomplete mapping between views. In Proceedings of the ACM conference on information and knowledge management (CIKM) (pp. 389-398).
9. Eriksson, A.; Olsson, C.; Kahl, F. (2007). Normalized cuts revisited: A reformulation for segmentation with linear grouping constraints. In Proceedings of the ICCV (pp. 1-8).
10. Farhadi, A.; Hejrati, M.; Sadeghi, M.; Young, P.; Rashtchian, C.; Hockenmaier, J.; et al. (2010). Every picture tells a story: Generating sentences from images. In Proceedings of the ECCV (Vol. 4, pp. 15-29).
11. Feng, S.; Manmatha, R.; Lavrenko, V. (2004). Multiple Bernoulli relevance models for image and video annotation. In Proceedings of the CVPR (Vol. 2, pp. 1002-1009).
12. Gajic, Z.; Qureshi, M. (Eds.). (1995). Lyapunov matrix equation in system stability and control. New York: Academic Press.
13. Ghanem, B.; Ahuja, N. (2010). Dinkelbach NCUT: An efficient framework for solving normalized cuts problems with priors and convex constraints. International Journal of Computer Vision, 89(1), 40-55.
14. Hoi, S.; Liu, W.; Lyu, M.; Ma, W. Y. (2006). Learning distance metrics with contextual constraints for image retrieval. In Proceedings of the CVPR (pp. 2072-2078).
15. Hotelling, H. (1936). Relations between two sets of variates. Biometrika, 28(3-4), 321-377.
16. Hubert, L.; Arabie, P. (1985). Comparing partitions. Journal of Classification, 2(1), 193-218.
17. Kamvar, S.; Klein, D.; Manning, C. (2003). Spectral learning. In Proceedings of the IJCAI (pp. 561-566).
18. Klein, D.; Kamvar, S.; Manning, C. (2002). From instance-level constraints to space-level constraints: Making the most of prior knowledge in data clustering. In Proceedings of the ICML (pp. 307-314).
19. Kulis, B.; Basu, S.; Dhillon, I.; Mooney, R. (2005). Semi-supervised graph clustering: A kernel approach. In Proceedings of the ICML (pp. 457-464).
20. Kulkarni, G.; Premraj, V.; Dhar, S.; Li, S.; Choi, Y.; Berg, A.; et al. (2011). Baby talk: Understanding and generating simple image descriptions. In Proceedings of the CVPR (pp. 1601-1608).
21. Lancaster, P. (1970). Explicit solutions of linear matrix equations. SIAM Review, 12(4), 544-566.
22. Law, M.; Topchy, A.; Jain, A. (2004). Clustering with soft and group constraints. In Proceedings of the joint IAPR international workshop on structural, syntactic, and statistical pattern recognition (pp. 662-670).
23. Li, Z.; Liu, J.; Tang, X. (2008). Pairwise constraint propagation by semidefinite programming for semi-supervised classification. In Proceedings of the ICML (pp. 576-583).
24. Li, J.; Wang, J. (2003). Automatic linguistic indexing of pictures by a statistical modeling approach. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(9), 1075-1088.
25. Liu, W.; Ma, S.; Tao, D.; Liu, J.; Liu, P. (2010). Semi-supervised sparse metric learning using alternating linearization optimization. In Proceedings of the KDD (pp. 1139-1148).
26. Lu, Z.; Carreira-Perpinan, M. (2008). Constrained spectral clustering through affinity propagation. In Proceedings of the CVPR.
27. Lu, Z.; Ip, H. (2009). Image categorization by learning with context and consistency. In Proceedings of the CVPR (pp. 2719-2726).
28. Lu, Z.; Ip, H. (2010). Constrained spectral clustering via exhaustive and efficient constraint propagation. In Proceedings of the ECCV (Vol, 6, pp. 1-14).
29. Lu, Z.; Ip, H.; Peng, Y. (2011). Contextual kernel and spectral methods for learning the semantics of images. IEEE Transactions on Image Processing, 20(6), 1739-1750.
30. Lu, Z.; Peng, Y.; Xiao, J. (2008). From comparing clusterings to combining clusterings. In Proceedings of the AAAI (pp. 665-670).
31. Ng, A.; Jordan, M.; Weiss, Y. (2002). On spectral clustering: Analysis and an algorithm. Advances in Neural Information Processing Systems, 14, 849-856.
32. Oliva, A.; Torralba, A. (2001). Modeling the shape of the scene: A holistic representation of the spatial envelope. International Journal of Computer Vision, 42(3), 145-175.
33. Ordonez, V.; Kulkarni, G.; Berg, T. (2012). Im2Text: Describing images using 1 million captioned photographs. Advances in Neural Information Processing Systems, 24, 1143-1151.
34. Rasiwasia, N.; Costa Pereira, J.; Coviello, E.; Doyle, G.; Lanckriet, G.; Levy, R.; et al. (2010). A new approach to cross-modal multimedia retrieval. In Proceedings of the ACM multimedia (pp. 251-260).
35. Rasiwasia, N.; Moreno, P.; Vasconcelos, N. (2007). Bridging the gap: Query by semantic example. IEEE Transactions on Multimedia, 9(5), 923-938.
36. Shi, J.; Malik, J. (2000). Normalized cuts and image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(8), 888-905.
37. Snoek, C.; Worring, M. (2005). Multimodal video indexing: A review of the state-of-the-art. Multimedia Tools and Applications, 25(1), 5-35.
38. Veksler, O. (2008). Star shape prior for graph-cut image segmentation. In Proceedings of the ECCV (pp. 454-467).
39. von Luxburg, U. (2007). A tutorial on spectral clustering. Statistics and Computing, 17(4), 395-416.
40. Wagstaff, K.; Cardie, C.; Rogers, S.; Schroedl, S. (2001). Constrained k-means clustering with background knowledge. In Proceedings of the ICML (pp. 577-584).
41. Xing, E.; Ng, A.; Jordan, M.; Russell, S. (2003). Distance metric learning with application to clustering with side-information. Advances in Neural Information Processing Systems, 15, 505-512.
42. Xu, L.; Li, W.; Schuurmans, D. (2009). Fast normalized cut with linear constraints. In Proceedings of the CVPR (pp. 2866-2873).
43. Yu, S.; Shi, J. (2004). Segmentation given partial grouping constraints. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(2), 173-183.
44. Zhou, D.; Bousquet, O.; Lal, T.; Weston, J.; Schölkopf, B. (2004). Learning with local and global consistency. Advances in Neural Information Processing Systems, 16, 321-328.
45. Zhu, X.; Ghahramani, Z.; Lafferty, J. (2003). Semi-supervised learning using Gaussian fields and harmonic functions. In Proceedings of the ICML (pp. 912-919).