Multilabel neighborhood propagation for region-based image retrieval

IEEE Transactions on Multimedia

Volumn 10, Issue 8, 2008, Pages 1592-1604

  Li, Fei ^a   Dai, Qionghai ^a   Xu, Wenli ^a   Er, Guihua ^a  

^a TSINGHUA NATIONAL LABORATORY FOR INFORMATION SCIENCE AND TECHNOLOGY   (China)

Author keywords

Label propagation; Manifold ranking; Region based image retrieval; Relevance feedback; Semi supervised learning

Indexed keywords

CONTENT BASED RETRIEVAL; CONTROL THEORY; EDUCATION; FEEDBACK; IMAGE SEGMENTATION; INFORMATION RETRIEVAL; INFORMATION THEORY; LABELS; LINEARIZATION; SUPERVISED LEARNING; SUPPORT VECTOR MACHINES;

LABEL PROPAGATION; MANIFOLD RANKING; REGION-BASED IMAGE RETRIEVAL; RELEVANCE FEEDBACK; SEMI-SUPERVISED LEARNING;

IMAGE RETRIEVAL;

EID: 57849096775     PISSN: 15209210     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMM.2008.2004914     Document Type: Article

References (43)

1. Y. Rui, T. S. Huang, and S. F. Chang, "Image retrieval: Current techniques, promising directions, and open issues." J. Vis. Commun. Image Represent., vol. 10, pp. 39-62, 1999.
2. M. Swain and D. Ballard, "Color indexing", Int. J. Comput. Vis., vol. 7, no. 1, pp. 11-32, 1991.
3. H. Tamura, S. Mori, and T. Yamawaki, "Texture features corresponding to visual perception", IEEE Trans. Syst., Man, Cybern., vol. 8, no. SMC-6. pp. 460-473, 1978.
4. A. K. Jain and A. Vailaya, "Shape-based retrieval: A case study with trademark image databases", Pattern Recognit., vol. 31, no. 9, pp. 1369-1390, 1998.
5. A. Smeulders, M. Worring, S. Santini, A. Gupta, and R. Jain, "Contentbased image retrieval at the end of the early years", IEEE Trans. Pattern Anal. Mack Intell., vol. 22, no. 12, pp. 1349-1380, 2000.
6. Y. Rui, T. S. Huang, M. Ortega, and S. Mehrotra, "Relevance feedback: A power tool for interactive content-based image retrieval", IEEE Trans. Circuits Syst. Video Technol., vol. 8, no. 5, pp. 644-655, 1998.
7. X. S. Zhou and T. S. Huang, "Relevance feedback for image retrieval: A comprehensive review", Multimedia Syst., vol. 8, pp. 536-544, 2003.
8. J. Z. Wang, J. Li, and G. Wiederhold, "SIMPLIcity: Semantics-sensitive integrated matching for picture libraries", IEEE Trans. Pattern Anal. Mack. Intell, vol. 23, no. 9, pp. 947-963, 2001.
9. C. Carson, S. Belongie, H. Greenspan, and J. Malik, "Blobworld: Image segmentation using expectation-maximization and its application to image querying", IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 8, pp. 1026-1038, 2002.
10. R. Datta, D. Joshi, J. Li, and J. Z. Wang, "Image retrieval: Ideas, influences, and trends of the new age", ACM Comput. Sunv., vol. 40, no. 2, pp. 1-60, 2008.
11. V. Vapnik, The Nature of Statistical Learning Theory. New York: Springer-Verlag, 1995.
12. S. Tong and E. Chang, "Support vector machine active learning for image retrieval", in Proc. ACM Int. Conf. Multimedia, 2001, pp. 107-118.
13. F. Jing, M. Li, H. J. Zhang, and B. Zhang, "An efficient and effective region-based image retrieval framework", IEEE Trans. Image Process., vol. 13, no. 5, pp. 699-709, 2004.
14. D. Tao, X. Tang, X. Li, and X. Wu, "Asymmetric bagging and random subspace for support vector machines-based relevance feedback in image retrieval", IEEE Trans. Pattern Anal. Mach. Intell., vol. 28, no. 7, pp. 1088-1099, 2006.
15. Y. Chen, J. Z. Wang, and R. Krovetz, "CLUE: Cluster-based retrieval of images by unsupervised learning", IEEE Trans. Image Process., vol. 14, no. 8, pp. 1187-1201, 2005.
16. R. Zhang and Z. M. Zhang, "Effective image retrieval based on hidden concept discovery in image database", IEEE Trans. Image Process., vol. 16, no. 2, pp. 562-572, 2007.
17. K. Lu, J. Zhao, and D. Cai, "An algorithm for semi-supervised learning in image retrieval", Pattern Recognit., vol. 39, pp. 717-720, 2006.
18. Z. Zhou, K. Chen, and H. Dai, "Enhancing relevance feedback in image retrieval using unlabeled data", ACM Trans. Inf. Syst., vol. 24, no. 2, pp. 219-244, 2006.
19. D. Zhou, O. Bousquet, T. N. Lal, J. Weston, and B. Schölkopf, "Learning with local and global consistency", in Advances in Neural Information Processing Systems, 2003.
20. X. Zhu, Z. Ghahramani, and J. Lafferty, "Semi-supervised learning using Gaussian fields and harmonic functions", in Proc. Int. Conf. Machine Learning, 2003.
21. M. Wang, T. Mei, X. Yuan, Y. Song, and L. R. Dai, "Video annotation by graph-based learning with neighborhood similarity", in Proc. ACM Int. Conf. Multimedia, 2007, pp. 325-328.
22. J. Tang, X. S. Hua, G. J. Qi, M. Wang, T. Mei, and X. Wu, "Structuresensitive manifold ranking for video concept detection", in Proc. ACM Int. Conf. Multimedia, 2007, pp. 852-861.
23. F. Wang and C. Zhang, "Label propagation through linear neighborhoods", in Proc. Int. Conf. Machine Learning, 2006.
24. X. Zhu and Z. Ghahramani, Learning From Labeled and Unlabeled Data With Label Propagation, Carnegie Mellon Univ., Pittsburgh, PA, Tech. Rep. CMU-CALD-02-107, 2002.
25. M. Szummer and T. Jaakkola, "Partially labeled classification with Markov random walks", in Advances in Neural Information Processing Systems, 2002.
26. D. Zhou, J. Weston, A. Gretton, O. Bousquet, and B. Schölkopf, "Ranking on data manifolds", in Advances in Neural Information Processing Systems, 2003.
27. J. He, M. Li, H. J. Zhang, H. Tong, and C. Zhang, "Manifold-ranking based image retrieval", in Proc. ACM Int. Conf. Multimedia, 2004, pp. 9-16.
28. J. He, M. Li, H. J. Zhang, H. Tong, and C. Zhang, "Generalized manifold-ranking-based image retrieval", IEEE Trans. Image Process., vol. 15, no. 10, pp. 3170-3177, 2006.
29. H. Tong, J. He, M. Li, W. Y. Ma, C. Zhang, and H. J. Zhang, "A unified optimization based learning method for image retrieval", in Proc. IEEE Int. Conf Computer Vision and Pattern Recognition, 2005, vol. 2, pp. 230-235.
30. J. Tang, X. S. Hua, G. J. Qi, and X. Wu, "Typicality ranking via semisupervised multiple-instance learning", in Proc. ACM Int. Conf. Multimedia, 2007, pp. 297-300.
31. Y. Rubner, C. Tomasi, and L. J. Guibas, "The earth mover's distance as a metric for image retrieval", Int. J. Comput. Vision, vol. 40, no. 2, pp. 99-121, 2000.
32. F. Kang, R. Jin, and R. Sukthankar, "Correlated label propagation with application to multi-label learning", in Proc. IEEE Int. Conf. Computer Vision and Pattern Recognition, 2006. vol. 2, pp. 1719-1726.
33. W. Jiang, G. Er, Q. Dai, and J. Gu, "Hidden annotation for image retrieval with long-term relevance feedback learning", Pattern Recognit., vol. 38, pp. 2007-2021, 2005.
34. Y. Deng, B. S. Manjunath, and H. Shin, "Color image segmentation", in Proc. IEEE Int. Conf. Computer Vision and Pattern Recognition, 1999, vol. 2, pp. 446-451.
35. F. Jing, M. Li, H. J. Zhang, and B. Zhang, "Relevance feedback in region-based image retrieval", IEEE Trans. Circuits Syst. Video Technol., vol. 14, no. 5, pp. 672-681, 2004.
36. Y. Liu, D. Zhang, G. Lu, and W. Y. Ma, "A survey of content-based image retrieval widi high-level semantics", Pattern Recognit., vol. 40, pp. 262-282, 2007.
37. W. Jiang, G. Er, Q. Dai, and J. Gu, "Similarity-based online feature selection in content-based image retrieval", IEEE Trans. Image Process., vol. 15, no. 3, pp. 702-712, 2006.
38. Y. X. Chen and J. Z. Wang, "A region-based fuzzy feature matching approach to content-based image retrieval", IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 9, pp. 1252-1267, 2002.
39. S. Santini and R. Jain, "Similarity measures", IEEE Trans. Pattern Anal Mack Intell., vol. 21, no. 9, pp. 871-883, 1999.
40. H. Tong, J. He, M. Li, C. Zhang, and W. Y. Ma, "Graph based multimodality learning", in Proc. ACM Int. Conf. Multimedia, 2005, pp. 862-871.
41. L. Fei-Fei, R. Fergus, and P. Perona, "Learning generative visual models from few training examples: An incremental Bayesian approach tested on 101 object categories", in IEEE CVPR Workshop on Generative-Model Based Vision, 2004.
42. M. H. C. Law, M. A. T. Figueiredo, and A. K. Jain, "Simultaneous feature selection and clustering using mixture models", IEEE Trans. Pattern Anal. Mach. Intell., vol. 26, no. 9, pp. 1154-1166, 2004.
43. W. Jiang, K. L. Chan, M. Li, and H. J. Zhang, "Mapping low-level features to high-level semantic concepts in region-based image retrieval", in Proc. IEEE Int. Conf. Computer Vision and Pattern Recognition, 2005, vol. 2, pp. 244-249.