Improving web image search by bag-based reranking

IEEE Transactions on Image Processing

Volumn 20, Issue 11, 2011, Pages 3280-3290

  Duan, Lixin ^a   Li, Wen ^a   Tsang, Ivor Wai Hung ^a   Xu, Dong ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Bag based image reranking; generalized multi instance (GMI) learning; text based image retrieval (TBIR)

Indexed keywords

GENERALIZED MULTI-INSTANCE (GMI) LEARNING; LEARNING METHODS; LEARNING PROBLEM; RANKING METHODS; RE-RANKING; REAL WORLD DATA; RELEVANCE FEEDBACK; RETRIEVAL PERFORMANCE; TEXT-BASED IMAGE RETRIEVALS; TEXTUAL QUERY; VISUAL FEATURE; WEB IMAGE SEARCH;

CONTENT BASED RETRIEVAL; EXPERIMENTS; FEEDBACK; USER INTERFACES; VIRTUAL REALITY; WORLD WIDE WEB;

INFORMATION RETRIEVAL;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; FACTUAL DATABASE; IMAGE ENHANCEMENT; INTERNET; METHODOLOGY; SEMANTICS;

ALGORITHMS; DATABASES, FACTUAL; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INTERNET; PATTERN RECOGNITION, AUTOMATED; SEMANTICS;

EID: 80054826786     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2011.2159227     Document Type: Article

References (42)

1. S. Andrews, I. Tsochantaridis, and T. Hofmann, "Support vector machines for multiple-instance learning," in Advances in Neural Information Processing Systems. Cambridge, MA: MIT Press, 2003, pp. 561-568.
2. R. C. Bunescu and R. J. Mooney, "Multiple instance learning for sparse positive bags," in Proc. 24th Int. Conf. Mach. Learn., 2007, pp. 105-112.
3. L. Chen, D. Xu, I. W. Tsang, and J. Luo, "Tag-based web photo retrieval improved by batch mode re-tagging," in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recogn., 2010, pp. 3440-3446.
4. T.-S. Chua, J. Tang, R. Hong, H. Li, Z. Luo, and Y.-T. Zheng, "NUSWIDE: A real-world web image database from national University of Singapore," in Proc. ACM Int. Conf. Image Video Retrieval, 2009, pp. 1-9.
5. J. Cui, F. Wen, and X. Tang, "Real time google and live image search re-ranking," in Proc. 16th ACM Int. Conf. Multimedia, 2008, pp. 729-732.
6. R. Datta, D. Joshi, J. Li, and J. Z.Wang, "Image retrieval: Ideas, influences, and trends of the new age," ACM Comput. Surv., vol. 40, no. 2, pp. 1-60, Apr. 2008.
7. T. Dietterich, R. Lathrop, and T. Lozano-Pérez, "Solving the multiple instance problem with axis-parallel rectangles," Artif. Intell., vol. 89, no. 1/2, pp. 31-71, Jan. 1997.
8. L. Duan, D. Xu, I. W. Tsang, and J. Luo, "Visual event recognition in videos by learning from web data," in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recogn., 2010, pp. 1959-1966.
9. P. Gehler and S. Nowozin, "Infinite kernel learning" Max Planck Inst. Biol. Cybern., Tuebingen, Germany, Tech. Rep. TR-178, 2008.
10. P. Gehler and S. Nowozin, "Let the kernel figure it out; principled learning of pre-processing for kernel classifiers," in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recog., 2009, pp. 2836-2843.
11. J. He, M. Li, H. Zhang, H. Tong, and C. Zhang, "Manifold-ranking based image retrieval," in Proc. ACM Multimedia, 2004, pp. 9-16.
12. W. H. Hsu, L. S. Kennedy, and S.-F. Chang, "Video search reranking via information bottleneck principle," in Proc. 14th ACM Int. Conf. Multimedia, 2006, pp. 35-44.
13. W. H. Hsu, L. S. Kennedy, and S.-F. Chang, "Video search reranking through random walk over document-level context graph," in Proc. 15th ACM Int. Conf. Multimedia, 2007, pp. 971-980.
14. Y. Jing and S. Baluja, "Pagerank for product image search," in Proc. 17th Int. Conf. World Wide Web, 2008, pp. 307-316.
15. J. E. Kelley, "The cutting plane method for solving convex programs," SIAM J. Appl. Math., vol. 8, no. 4, pp. 703-712, Dec. 1960.
16. S.-J. Kim and S. Boyd, "A minimax theorem with applications to machine learning, signal processing, and finance," SIAM J. Optim., vol. 19, no. 3, pp. 1344-1367, 2008.
17. Y.-F. Li, J. T. Kwok, I. W. Tsang, and Z.-H. Zhou, "A convex method for locating regions of interest with multi-instance learning," in Proc. Eur. Conf. Mach. Learn. Principles Pract. Knowl. Discovery Databases, 2009, pp. 15-30.
18. Y.-F. Li, I. W. Tsang, J. T. Kwok, and Z.-H. Zhou, "Tighter and convex maximum margin clustering," in Proc. 22nd Int. Conf. Artif. Intell. Stat., 2009, pp. 344-351.
19. Y. Liu, D. Xu, I. W. Tsang, and J. Luo, "Textual query of personal photos facilitated by large-scale web data," IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 5, pp. 1022-1036, May 2011.
20. O. Maron and T. Lonzano-Pérez, "A framework for multiple-instance learning," in Advances in Neural Information Processing Systems. Cambridge, MA: MIT Press, 1998, pp. 570-576.
21. O. Maron and A. L. Ratan, "Multiple-instance learning for natural scene classification," in Proc. 15th Int. Conf. Mach. Learn., 1998, pp. 341-349.
22. A. Rakotomamonjy, F. R. Bach, and Y. Grandvalet, "SimpleMKL," J. Mach. Learn. Res., vol. 9, pp. 2491-2521, 2008.
23. Y. Rui, T. S. Huang, and S. Mehrotra, "Content-based image retrieval with relevance feedback in MARS," in Proc. IEEE Int. Conf. Image Process., 1997, pp. 815-818.
24. D. W. Scott, Multivariate Density Estimation: Theory, Practice, and Visualization. New York: Wiley-Interscience, 1992.
25. S. Scott, J. Zhang, and J. Brown, "On generalized multiple-instance learning," Int. J. Comput. Intell. Appl., vol. 5, pp. 21-35, 2005.
26. N. Slonim, N. Friedman, and N. Tishby, "Unsupervised document classification using sequential information maximization," in Proc. 25th Annu. Int. ACM SIGIR Conf. Res. Develop. Inf. Retrieval, 2002, pp. 129-136.
27. A. W. M. Smeulders, M.Worring, S. Santini, and A. Gupta, "Contentbased image retrieval at the end of the early years," IEEE Trans. Pattern Anal. Mach. Intell., vol. 22, no. 12, pp. 1349-1380, Dec. 2000.
28. Q. Tao and S. Scott, "A faster algorithm for generalized multiple-instance learning," in Proc. 17th Int. Florida Artif. Intell. Res. Soc. Conf., 2004, pp. 550-555.
29. Q. Tao, S. D. Scott, N. V. Vinodchandran, and T. T. Osugi, "SVM-based generalized multiple-instance learning via approximate box counting," in Proc. 21st Int. Conf. Mach. Learn., 2004, pp. 779-806.
30. Q. Tao, S. D. Scott, N. V. Vinodchandran, T. T. Osugi, and B. Mueller, "Kernels for generalized multiple-instance learning," IEEE Trans. Pattern Anal. Mach. Intell., vol. 30, no. 12, pp. 2084-2098, Dec. 2008.
31. X. Tian, D. Tao, X.-S. Hua, and X. Wu, "Active reranking for web image search," IEEE Trans. Image Process., vol. 19, no. 3, pp. 805-820, Mar. 2010.
32. X. Tian, L. Yang, J. Wang, Y. Yang, X. Wu, and X.-S. Hua, "Bayesian video search reranking," in Proc. 16th ACM Int. Conf. Multimedia, 2008, pp. 131-140.
33. S. Tong and E. Chang, "Support vector machine active learning for image retrieval," in Proc. 9th ACM Int. Conf. Multimedia, 2001, pp. 107-118.
34. S. Vijayanarasimhan and K. Grauman, "Keywords to visual categories: Multiple-instance learning for weakly supervised object categorization," in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recog., 2008, pp. 1-8.
35. J. Wang and J.-D. Zucker, "Solving the multiple-instance problem: A lazy learning approach," in Proc. 17th Int. Conf. Mach. Learn., 2000, pp. 1119-1125.
36. S.Wang, Q. Huang, S. Jiang, L. Qin, and Q. Tian, "Visual contextrank for web image re-ranking," in Proc. 1st ACM Workshop Large-Scale Multimedia Retrieval Mining, 2009, pp. 121-128.
37. R. Yan, A. G. Hauptmann, and R. Jin, "Multimedia search with pseudorelevance feedback," in Proc. ACM Int. Conf. Image Video Retrieval, 2003, pp. 238-247.
38. C. Zhang, J. Y. Chai, and R. Jin, "User term feedback in interactive text-based image retrieval," in Proc. 28th Annu. Int. ACM SIGIR Conf. Res. Develop. Inf. Retrieval, 2005, pp. 51-58.
39. L. Zhang, F. Lin, and B. Zhang, "Support vector machine learning for image retrieval," in Proc. IEEE Int. Conf. Image Process., 2001, pp. 721-724.
40. Q. Zhang and S. A. Goldman, "EM-DD: An improved multiple-instance learning technique," in Advances in Neural Information Processing Systems. Cambridge, MA: MIT Press, 2002, pp. 1073-1080.
41. Q. Zhang, S. A. Goldman, W. Yu, and J. E. Fritts, "Content-based image retrieval using multiple-instance learning," in Proc. 19th Int. Conf. Mach. Learn., 2002, pp. 682-689.
42. Z.-H. Zhou and H.-B. Dai, "Exploiting image contents in web search," in Proc. 20th Int. Joint Conf. Artif. Intell., 2007, pp. 2928-2933.