Similarity-based online feature selection in content-based image retrieval

IEEE Transactions on Image Processing

Volumn 15, Issue 3, 2006, Pages 702-712

  Jiang, Wei ^a   Er, Guihua ^a   Dai, Qionghai ^a   Gu, Jinwei ^a  

^a TSINGHUA UNIVERSITY   (China)

Author keywords

Boosting; Online feature selection; Region based image retrieval; Relevance feedback

Indexed keywords

ALGORITHMS; FAST RESPONSE COMPUTER SYSTEMS; FEEDBACK CONTROL; FUZZY SETS; LEARNING SYSTEMS; ONLINE SEARCHING; SEMANTICS;

BOOSTING; CONTENT-BASED IMAGE RETRIEVAL; ONLINE FEATURE SELECTION; RELEVANCE FEEDBACK;

CONTENT BASED RETRIEVAL;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; EVALUATION; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; INFORMATION RETRIEVAL; METHODOLOGY; ONLINE SYSTEM;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INFORMATION STORAGE AND RETRIEVAL; ONLINE SYSTEMS; PATTERN RECOGNITION, AUTOMATED; SUBTRACTION TECHNIQUE;

EID: 32944455697     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2005.863105     Document Type: Article

References (38)

1. J. Bilmes, "A gentle tutorial on the EM algorithm and its application to parameter estimation for Gaussian mixture and hidden Markov models," Int. Comput. Sci. Inst. (ICSI), Berkeley, CA, Tech. Rep. ICSI-TR-97-021, 1997.
2. M. Brand, "Incremental singular value decomposition of uncertain data with missing values," in Proc. Eur. Conf. Computer Vision, vol. 2350, Copenhagen, Denmark, 2002, pp. 707-720.
3. C. Carson, M. Thomas, S. Belongie, J. M. Hellerstein, and J. Malik, "Blobworld: A system for region-based image indexing and retrieval," in Proc. Int. Conf. Visual Information Systems, Amsterdam, The Netherlands, 1999, pp. 509-516.
4. 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, Aug. 2002.
5. Y. Q. Chen, X. Z. Zhou, and T. S. Huang, "One-class SVM for learning in image retrieval," in Proc. IEEE Int. Conf. Image Processing, vol. 1, Thessaloniki, Greece, 2001, pp. 34-37.
6. Y. X. Chen and J. Z. Wang, "A region-based fuzzy feature matching approach for content-based image retrieval," IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 9, pp. 1252-1267, Sep. 2002.
7. Corel stock photo library, Ontario, Canada: Corel.
8. Y. Deng, B. S. Manjunath, and H. Shin, "Color image segmentation," in Proc. Int. Conf. Computer Vision Pattern Recognition, vol. 2, Ft. Collins, CO, 1999, pp. 446-451.
9. Y. Freund and R. Schapire, "Experiments with a new boosting algorithm," in Proc. Int. Conf. Machine Learning, Bari, Italy, 1996, pp. 148-156.
10. J. Friedman, T. Hastie, and R. Tibshirani, "Additive logistic regression: A statistical view of boosting," Ann. Stat., vol. 38, no. 2, pp. 337-374, 2000.
11. K. Fukunaga, Introduction to Statistical Pattern Recognition, 2nd ed. New York: Academic, 1990.
12. G. D. Guo, A. K. Jain, W. Y. Ma, and H. J. Zhang, "Learning similarity measures for natural image retrieval with relevance feedback," IEEE Trans. Neural Networks, vol. 13, no. 4, pp. 811-820, Apr. 2002.
13. P. Hong, Q. Tian, and T. S. Huang, "Incorporate support vector machines to content-based image retrieval with relevant feedback," in Proc. Int. Conf. Image Processing, vol. 3, Vancouver, BC, Canada, 2000, pp. 750-753.
14. T. S. Huang, X. S. Zhou, M. Nakazato, Y. Wu, and I. Cohen, "Learning in content-based image retrieval," in Proc. IEEE Int. Conf. Development and Learning, Cambridge, MA, 2002, pp. 155-162.
15. F. Jing, M. J. Li, H. J. Zhang, and B. Zhang, "An effective and efficient region-based image retrieval framework," IEEE Trans. Image Process., vol. 13, no. 5, pp. 699-709, May 2004.
16. T. Joachims, "Making large-scale SVM learning practical," in Advances in Kernel Methods - Support Vector Learning, B. Scholkopf, C. Burges, and A. Smola, Eds. Cambridge, MA: MIT Press, 1999.
17. M. Jordan, Ed., Learning in Graphical Models. Cambridge, MA: MIT-Press, 1999.
18. J. M. Keller, M. R. Gray, and J. A. Givens, "A fuzzy k-nearest neighbor algorithm," IEEE Trans. Syst., Man Cybern., vol. SMC-15, no. 4, pp. 580-585, Apr. 1985.
19. 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, Sep. 2004.
20. C. Liu and H. Y. Shum, "Kullback-Leibler boosting," in Proc. Int. Conf. Computer Vision Pattern Recognition, vol. 1, 2003, pp. 587-594.
21. T. P. Minka and R. W. Picard, "Interactive learning using a society of models," Pattern Recognit., vol. 30, no. 4, pp. 565-581, 1997.
22. Y. Rui, T. S. Huang, M. Ortega, and S. Mehrotra, "Relevance feedback: A powerful tool in interactive content-based image retrieval," IEEE Trans. Circuits Syst. Video Technol., vol. 8, no. 5, pp. 644-655, May 1998.
23. S. Santini and R. Jain, "Similarity measures," IEEE Trans. Pattern Anal. Mach. Intell., vol. 21, no. 9, pp. 871-883, Sep. 1999.
24. A. W. M. Smeulders, M. Worring, S. Santini, A. Gupta, and R. Jain, "Content-based image retrieval at the end of the ealy years," IEEE Trans. Pattern Anal. Mach. Intell., vol. 22, no. 12, pp. 1349-1380, Dec. 2002.
25. J. B. Tenenbaum and T. L. Griffiths, "Generalization, similarity, and Bayesian inference," Behav. Brain Sci., vol. 24, pp. 629-640, 2001.
26. H. Tamura, S. Mori, and T. Yamawaki, "Texture features corresponding to visual perception," IEEE Trans. Syst. Man Cybern., vol. SMC-8, no. 6, pp. 460-473, 1978.
27. K. Tieu and P. Viola, "Boost image retrieval," in Proc. Int. Conf. Computer Vision Pattern Recognition, vol. 1, Hilton Head Island, SC, 2000, pp. 228-235.
28. S. Tong and E. Chang, "Support vector machine active learning for image retrieval," in Proc. ACM Multimedia, Ottawa, ON, Canada, 2001.
29. K. Torkkola, "Feature extraction by nonparametric mutual information maximization," J. Mach. Learn. Res., vol. 3, pp. 1415-1438, 2003.
30. A. Tvesky, "Feature of similarity," Psychol. Rev., vol. 84, no. 4, pp. 327-352, 1977.
31. N. Vasconcelos and A. Lippman, "Learning from user feedback in image retrieval system," in Proc. NIPS, Denver, CO, 1999, pp. 977-983.
32. L. Wang, K. L. Chan, and Z. H. Zhang, "Bootstrapping SVM active learning by incorporating unlabeled images for image retrieval," in Proc. IEEE Int. Conf. Computer Vision Pattern Recognition, vol. 1, 2003, pp. 629-634.
33. Y. Wu, Q. Tian, and T. S. Huang, "Discriminant EM algorithm with application to image retrieval," in Proc. Int. Conf. Computer Vision Pattern Recognition, vol. 1, 2000, pp. 222-227.
34. L. Zhang, F. Z. Lin, and B. Zhang, "Support vector machine learning for image retrieval," in Proc. Int. Conf. Image Processing, vol. 2, Thessaloniki, Greece, 2001, pp. 721-724.
35. W. D. Zhang and T. H. Chen, "Classification based on symmetric maximized minimal distance in subspace (SMMS)," in Proc. Int. Conf. Computer Vision Pattern Recognition, vol. 2, 2003, pp. 100-105.
36. R. F. Zhang and Z. F. Zhang, "Hidden semantic concept discovery in region based image retrieval," in Proc. Int. Conf. Computer Vision Pattern Recognition, vol. 2, Washington, DC, 2004, pp. 996-1001.
37. X. S. Zhou and T. S. Huang, "Small sample learning during multimedia retrieval using BiasMap," in Proc. Int. Conf. Computer Vision Pattern Recognition, vol. 1, 2001, pp. 11-17.
38. H. J. Zimmermann, Fuzzy Set Theory and Its Applications, 2nd ed. Boston, MA: Kluwer, 1991.