Kernel-based distance metric learning for content-based image retrieval

Image and Vision Computing

Volumn 25, Issue 5, 2007, Pages 695-703

  Chang, Hong ^a   Yeung, Dit Yan ^a  

^a HONG KONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Hong Kong)

Author keywords

Content based image retrieval; Kernel method; Metric learning; Relevance feedback

Indexed keywords

DATABASE SYSTEMS; DISTANCE EDUCATION; FEATURE EXTRACTION; IMAGE ANALYSIS; INFORMATION ANALYSIS; LEARNING SYSTEMS; MATHEMATICAL TRANSFORMATIONS;

IMAGE DATABASES; KERNEL METHOD; METRIC LEARNING; RELEVANCE FEEDBACK;

CONTENT BASED RETRIEVAL;

EID: 33847024933     PISSN: 02628856     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.imavis.2006.05.013     Document Type: Article

References (27)

1. Smeulders A., Worring M., Santini S., Gupta A., and Jain R. Content-based image retrieval at the end of the early years. IEEE Transactions on Pattern Analysis and Machine Intelligence 22 12 (2000) 1349-1380
2. Swain M.J., and Ballard D.H. Color indexing. International Journal of Computer Vision 7 1 (1991) 11-32
3. Hafner J., Sawhney H.S., Equitz W., Flickner M., and Niblack W. Efficient color histogram indexing for quadratic from distance functions. IEEE Transactions on Pattern Analysis and Machine Intelligence 17 7 (1995) 729-736
4. M. Stricker, M. Orengo, Similarity of color images, in: Storage and Retrieval for Image and Video Databases (SPIE), vol. 2, 1995, pp. 381-392.
5. Rui Y., Huang T.S., Ortega M., and Mehrotra S. Relevance feedback: a power tool for interactive content-based image retrieval. IEEE Transactions on Circuits and Systems for Video Technology 8 5 (1998) 644-655
6. Y. Ishikawa, R. Subramanya, C. Faloutsos, Mindreader: query databases through multiple examples, in: Proceedings of the 24th VLDB Conference, 1998.
7. Doulamis A., Doulamis N., and Varvarigou T. Efficient content-based image retrieval using fuzzy organization and optimal relevance feedback. International Journal of Image and Graphics 3 1 (2003) 171-208
8. D.R. Heisterkamp, J. Peng, H.K. Dai, Adaptive quasiconformal kernel metric for image retrieval, in: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, 2001, pp. 388-393.
9. A. Dong, B. Bhanu, A new semi-supervised EM algorithm for image retrieval, in: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, 2003, pp. 662-667.
10. Yang J., Li Q., and Zhuang Y. Towards data-adaptive and user-adaptive image retrieval by peer indexing. International Journal of Computer Vision 56 1/2 (2004) 47-63
11. X. He, Incremental semi-supervised subspace learning for image retrieval, in: Proceedings of the 12th Annual ACM International Conference on Multimedia, 2004, pp. 2-8.
12. X. He, W.Y. Ma, H.J. Zhang, Learning an image manifold for retrieval, in: Proceedings of the 12th Annual ACM International Conference on Multimedia, 2004, pp. 17-23.
13. X.S. Zhou, T.S. Huang, Small sample learning during multimedia retrieval using biasmap, in: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2001, pp. 11-17.
14. Guo G., Jain A.K., Ma W., and Zhang H. Learning similarity measure for natural image retrieval with relevance feedback. IEEE Transactions on Neural Networks 13 4 (2002) 811-820
15. D. Tao, X. Tang, Random sampling based SVM for relevance feedback image retrieval, in: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, 2004, pp. 647-652.
16. S. Tong, E. Chang, Support vector machine active learning for image retrieval, in: Proceedings of the Ninth ACM International Conference on Multimedia, 2001, pp. 107-118.
17. Tieu K., and Viola P. Boosting image retrieval. International Journal of Computer Vision 56 1/2 (2004) 17-36
18. A. Bar-Hillel, T. Hertz, N. Shental, D. Weinshall, Learning distance functions using equivalence relations, in: Proceedings of the Twentieth International Conference on Machine Learning, Washington, DC, USA, 21-24 August 2003, pp. 11-18.
19. T. Hertz, N. Shental, A. Bar-Hillel, D. Weinshall, Enhancing image and video retrieval: learning via equivalence constraints, in: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, Madison, WI, USA, 18-20 June 2003, pp. 668-674.
20. K. Wagstaff, C. Cardie, S. Rogers, S. Schroedl, Constrained k-means clustering with background knowledge, in: Proceedings of the Eighteenth International Conference on Machine Learning, Williamstown, MA, USA, 2001, pp. 577-584.
21. Xing E.P., Ng A.Y., Jordan M.I., and Russell S. Distance metric learning with application to clustering with side-information. In: Becker S., Thrun S., and Obermayer K. (Eds). Advances in Neural Information Processing Systems vol. 15 (2003), MIT Press, Cambridge, MA, USA 505-512
22. T. Hertz, A. Bar-Hillel, D. Weinshall, Boosting margin based distance functions for clustering, in: Proceedings of the Twenty-First International Conference on Machine Learning, Banff, Alberta, Canada, 4-8 August 2004, pp. 393-400.
23. T. Hertz, A. Bar-Hillel, D. Weinshall, Learning distance functions for image retrieval, in: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, Washington, DC, USA, 27 June-3 July 2004, pp. 570-577.
24. He X., King O., Ma W.Y., Li M., and Zhang H.J. Learning a semantic space from user's relevance feedback. IEEE Transactions on Circuits and Systems for Video Technology 13 1 (2003) 39-48
25. C.H. Hoi, M.R. Lyu, A novel log-based relevance feedback technique in content-based image retrieval, in: Proceedings of the 12th Annual ACM International Conference on Multimedia, 2004, pp. 24-31.
26. Schölkopf B., Smola A.J., and Müller K.-R. Nonlinear component analysis as a kernel eigenvalue problem. Neural Computation 10 (1998) 1299-1319
27. G. Pass, R. Zabih, J. Miller, Comparing images using color coherence vectors, in: Proceedings of the Fourth ACM International Conference on Multimedia, 1996, pp. 65-73.