Hidden-concept driven multilabel image annotation and label ranking

IEEE Transactions on Multimedia

Volumn 14, Issue 1, 2012, Pages 199-210

  Bao, Bing Kun ^a   Li, Teng ^a   Yan, Shuicheng ^b  

^a INSTITUTE OF AUTOMATION   (China)

^b NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

Image annotation; label ranking; nonnegative data factorization

Indexed keywords

IMAGE ANNOTATION; IMAGE DATASETS; IMAGE REGIONS; IMAGE REPRESENTATIONS; LABEL PROPAGATION; LABELED AND UNLABELED DATA; LINEAR COEFFICIENTS; LINEAR COMBINATIONS; MULTI-LABEL; OBJECTIVE FUNCTIONS; RANKING ALGORITHM; RANKING PROBLEMS; SEMI-SUPERVISED;

ALGORITHMS; FACTORIZATION; IMAGE ANALYSIS;

IMAGE CODING;

EID: 84862960217     PISSN: 15209210     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMM.2011.2170557     Document Type: Article

References (45)

1. J. Yuan, J. Li, and B. Zhang, "Exploiting spatial context constraints for automatic image region annotation," in Proc. 15th ACM Int. Conf. Multimedia, 2007, pp. 595-604.
2. [Online]. Available: http://wordnet.princeton.edu
3. G. Chen, Y. Song, F. Wang, and C. Zhang, "Semi-supervised multilabel learning by solving a sylvester equation," in Proc. SIAM Int. Conf Data Mining, Atlanta, GA, 2008, pp. 410-419.
4. Y. Liu, R. Jin, and L. Yang, "Semi-supervised multi-label learning by constrained non-negative matrix factorization," in Proc. Nat. Conf. Artif. Intell. Innovative Applic. Artif. Intelligence Conf., 2006, vol. 21, pp. 666-671.
5. X. Xu and E. Frank, "Logistic regression and boosting for labeled bags of instances," in Proc. Pacific Asia Conf. Knowledge Discovery and Data Mining, 2004, pp. 272-281. (Pubitemid 38824910)
6. Y. Chen, J. Bi, and J. Z. Wang, "Miles: Multiple-instance learning via embedded instance selection," IEEE Trans. Pattern Anal. Mach. Intell., vol. 28, no. 12, pp. 1931-1947, Dec. 2006. (Pubitemid 46405705)
7. Z. Zhou and M. Zhang, "Multi-instance multi-label learning with application to scene classification," Adv. Neural Inf. Process. Syst., vol. 19, pp. 1609-1616, 2007.
8. B. Cheng, J. Yang, S. Yan, Y. Fu, and T. Huang, "Learning with l1-graph for image analysis," IEEE Trans. Image Process., vol. 19, no. 4, pp. 858-866, Apr. 2010.
9. Y. Rui, T. S. Huang, and S. F. Chang, "Image retrieval: Current techniques, promising directions, and open issues," J. Vis. Commun. Image Representation, vol. 10, no. 1, pp. 39-62, 1999.
10. S. Zhu, X. Ji,W. Xu, and Y. Gong, "Multi-labelled classification using maximum entropy method," in Proc. 28th Annu. Int. ACMSIGIR Conf., 2005, pp. 274-281.
11. N. Ueda and K. Saito, "Parametric mixture models for multi-labeled text," in Proc. Neural Inf. Process. Syst. Conf., 2003, pp. 721-728.
12. K. Barnard and D. Forsyth, "Learning the semantics of words and pictures," in Proc. 8th Int. Conf. Comput. Vis., 2001, vol. 2, pp. 408-415. (Pubitemid 32795085)
13. J. Fan, Y. Gao, H. Luo, and R. Jain, "Mining multilevel image semantics via hierarchical classification," IEEE Trans. Multimedia, vol. 10, no. 2, pp. 167-187, Apr. 2008.
14. N. Vasconcelos, "Image indexing with mixture hierarchies," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2001, vol. 1.
15. J. Luo, A. E. Savakis, and A. Singhal, "A bayesian network-based framework for semantic image understanding," Pattern Recognit., vol. 38, no. 6, pp. 919-934, 2005. (Pubitemid 40308639)
16. L. Fei-Fei and P. Perona, "A bayesian hierarchical model for learning natural scene categories," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2005, vol. 2, pp. 524-531.
17. J. Sivic, B. C. Russell, A. A. Efros, A. Zisserman, and W. T. Freeman, "Discovering objects and their location in images," in Proc. IEEE Int. Conf. Comput. Vis., 2005, vol. 1, pp. 370-377. (Pubitemid 44054982)
18. T. Li, S. Yan, T. Mei, X.-S. Hua, and I.-S. Kweon, "Image decomposition with multilabel context: Algorithms and applications," IEEE Trans. Image Process., vol. 20, no. 8, pp. 1057-7149, Aug. 2011.
19. B. Yao and L. Fei-Fei, "Modeling mutual context of object and human pose in human-object interaction activities," in Proc. IEEE Comput. Vis. Pattern Recognit., 2010.
20. B. K. Bao, B. Ni, Y. Mu, and S. Yan, "Efficient region-aware large graph construction towards scalable multi-label propagation," Pattern Recognit., vol. 44, no. 3, pp. 598-606, 2011.
21. G. J. Qi, X. S. Hua, Y. Rui, J. Tang, T. Mei, and H. J. Zhang, "Correlative multi-label video annotation," in Proc. 15th ACM Int. Conf. Multimedia, 2007, pp. 17-26.
22. E. Hüllermeier, J. Fürnkranz, W. Cheng, and K. Brinker, "Label ranking by learning pairwise preferences," Artif. Intell., vol. 172, no. 16-17, pp. 1897-1916, 2008.
23. S. Har-peled, D. Roth, and D. Zimak, "Constraint classification: A new approach to multiclass classification and ranking," Adv. Neural Inf. Process. Syst., pp. 267-280, 2002.
24. D. Liu, X. S. Hua, L. Yang, M. Wang, and H. J. Zhang, "Tag ranking," in Proc. 18th Int. Conf. World Wide Web, 2009, pp. 351-360.
25. D. D. Lee and H. S. Seung, "Learning the parts of objects by non-negative matrix factorization," Nature, vol. 401, no. 6755, pp. 788-791, 1999.
26. J. Wright, A. Y. Yang, A. Ganesh, S. S. Sastry, and Y. Ma, "Robust face recognition via sparse representation," IEEE Trans. Pattern Anal. Mach. Intell., vol. , pp. 210-227, 2008.
27. D. L. Donoho, "For most large underdetermined systems of linear equations the minimal l1-norm solution is also the sparsest solution," Commun. Pure Appl. Math., vol. 59, no. 6, pp. 797-826, 2006.
28. B. K. Bao, T. Li, and S. Yan, "Hidden-concept driven image decomposition towards semi-supervised multi-label image annotation," in Proc. Int. Conf. Internet Multimedia Computing and Service, 2009, pp. 17-22.
29. Y. Rui, T. S. Huang, and S. F. Chang, "Image retrieval: Current techniques, promising directions, and open issues 1," J. Vis. Commun. Image Representation, vol. 10, no. 1, pp. 39-62, 1999.
30. B. Sigurbjornsson and R. Van Zwol, "Flickr tag recommendation based on collective knowledge," in Proc. 17th Int. Conf. World Wide Web, 2008, pp. 327-336.
31. X. Liu, S. Yan, J. Yan, and H. Jin, "Unified solution to nonnegative data factorization problems," in Proc. IEEE Int. Conf. Data Mining, 2009, pp. 307-316.
32. J. Shotton, J. Winn, C. Rother, and A. Criminisi, "Textonboost: Joint appearance, shape and context modeling for multi-class object recognition and segmentation," in Proc. 9th Eur. Conf. Comput. Vis., 2006, vol. 3954, pp. 1-15. (Pubitemid 44029764)
33. T. S. Chua, J. Tang, R. Hong, H. Li, Z. Luo, and Y. Zheng, "Nuswide: A real-world web image database from national university of singapore," in Proc. ACM Conf. Image Video Retrieval, 2009, pp. 1-9.
34. S. Nowak, H. Lukashevich, P. Dunker, and S. Ruger, "Performance measures for multilabel evaluation: A case study in the area of image classification," in Proc. Int. Conf. Multimedia Inf. Retrieval, 2010, pp. 35-44.
35. [Online]. Available: http://www.flickr.com
36. J. Zhang, M. Marsza, and C. Lazebnik, "Local features and kernels for classification of texture and object categories:Acomprehensive study," Int. J. Comput. Vis., vol. 73, no. 2, pp. 213-238, 2007. (Pubitemid 46181625)
37. D. Marr, Vision: A Computational Investigation Into the Human Representation and Processing of Visual Information. New York: Holt, 1982.
38. D. G. Lowe, "Distinctive image features from scale-invariant keypoints," Int. J. Comput. Vis., vol. 60, no. 2, pp. 91-110, 2004.
39. J. A. Hanley and B. J.McNeil, "The meaning and use of the area under a receiver operating characteristic (roc) curve," Radiology, vol. 143, no. 1, pp. 29-36, 1982. (Pubitemid 12142173)
40. K. Jarvelin and J. Kekalainen, "Cumulated gain-based evaluation of IR techniques," ACM Trans. Inf. Syst., vol. 20, no. 4, pp. 422-446, 2002. (Pubitemid 44642296)
41. H.Wang, H. Huang, and C. Ding, "Image annotation using multi-label correlated Green's function," in Proc. IEEE 12th Int. Conf. Comput. Vis., 2009, pp. 2029-2034.
42. D. D. Lee and H. S. Seung, "Algorithms for non-negative matrix factorization," Adv. Neural Inf. Process. Syst., pp. 556-562, 2001.
43. H. W. Kuhn and A. W. Tucker, Nonlinear Programming. Berkely, CA: Univ. of California, 1951.
44. R. Tibshirani, "Regression shrinkage and selection via the lasso," J. Royal Stat. Soc. B, vol. 58, no. 1, pp. 267-288, 1996.
45. J. Liu and J. Ye, "Efficient euclidean projections in linear time," in Proc. 26th Int. Conf. Mach. Learning, 2009, pp. 657-664.