Large-scale image annotation by efficient and robust kernel metric learning

Proceedings of the IEEE International Conference on Computer Vision

Volumn , Issue , 2013, Pages 1609-1616

  Feng, Zheyun ^a   Jin, Rong ^a   Jain, Anil ^a  

^a Michigan State University   (United States)

Author keywords

Efficient; Image Annotation; Kernel Metric Learning; Regression; Theoretical guarantee

Indexed keywords

IMAGE ANALYSIS; REGRESSION ANALYSIS; SEMANTICS;

EFFICIENT; IMAGE ANNOTATION; METRIC LEARNING; REGRESSION; THEORETICAL GUARANTEES;

LEARNING ALGORITHMS;

EID: 84898790932     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2013.203     Document Type: Conference Paper

References (35)

1. A. Bar-Hillel, T. Hertz, N. Shental, and D. Weinshall. Learning a mahalanobis metric from equivalence constraints. JMLR, 6:937-965, 2005.
2. G. Baudat and F. Anouar. Generalized discriminant analysis using a kernel approach. Neural Computation, 12(10):2385-2404, 2000.
3. G. Carneiro, A. B. Chan, P. J. Moreno, and N. Vasconcelos. Supervised learning of semantic classes for image annotation and retrieval. PAMI, 29(3):394-410, 2007.
4. G. Chechik, V. Sharma, U. Shalit, and S. Bengio. Large scale online learning of image similarity through ranking. JMLR, 11:1109-1135, 2010.
5. J. Chen, Z. Zhao, J. Ye, and H. Liu. Nonlinear adaptive distance metric learning for clustering. In KDD, 2007.
6. R. Chitta, R. Jin, and A. K. Jain. Efficient kernel clustering using random fourier features. In ICDM, 2012.
7. J. Davis, B. Kulis, P. Jain, S. Sra, and I. Dhillon. Informationtheoretic metric learning. In ICML, 2007.
8. P. Drineas and M. W. Mahoney. On the nystr̈om method for approximating a gram matrix for improved kernel-based learning. JMLR, 6:2153-2175, 2005.
9. J. Fan, Y. Gao, and H. Luo. Multi-level annotation of natural scenes using dominant image components and semantic concepts. In ACM Multimedia, 2004.
10. S. L. Feng, R. Manmatha, and V. Lavrenko. Multiple bernoulli relevance models for image and video annotation. In CVPR, 2004.
11. S. Gao, Z. Wang, L.-T. Chia, and I. W.-H. Tsang. Automatic image tagging via category label and web data. In ACM Multimedia, 2010.
12. M. Guillaumin, T. Mensink, J. Verbeek, and C. Schmid. TagProp: discriminative metric learning in nearest neighbor models for image auto-annotation. In ICCV, 2009.
13. M. Guillaumin, J. Verbeek, and C. Schmid. Is that you? metric learning approaches for face identification. In ICCV, 2009.
14. T. Hertz, A.-B. Hillel, and D. Weinshall. Boosting margin based distance functions for clustering. In ICML, 2004.
15. T. Hertz, A.-B. Hillel, and D. Weinshall. Learning a kernel function for classification with small training samples. In ICML, 2006.
16. S. Hoi, W. Liu, M. Lyu, and W. Ma. Learning distance metrics with contextual constraints for image retrieval. In CVPR, 2006.
17. C. Ji, X. Zhou, L. Lin, and W. Yang. Labeling images by integrating sparse multiple distance learning and semantic context modeling. In ECCV, 2012.
18. R. Jin, S. Wang, and Y. Zhou. Regularized distance metric learning:theory and algorithm. In NIPS. 2009.
19. Landauer. Handbook of Latent Semantic Analysis. Lawrence Erlbaum Associates, 2007.
20. X. Li, C. G. Snoek, and M. Worring. Learning social tag relevance by neighbor voting. IEEE Transactions on Multimedia, 11(7):1310-1322, 2009.
21. A. Makadia, V. Pavlovic, and S. Kumar. A new baseline for image annotation. In ECCV, 2008.
22. T. Mensink, J. J. Verbeek, and G. Csurka. Learning structured prediction models for interactive image labeling. In CVPR, 2011.
23. C. A. Micchelli, Y. Xu, and H. Zhang. Universal kernels. JMLR, 6:2651-2667, 2006.
24. B. Scḧolkopf and A. J. Smola. Learning with kernels: support vector machines, regularization, optimization and beyond. MIT Press, 2002.
25. B. Scḧolkopf, A. J. Smola, and K.-R.M̈uller. Nonlinear component analysis as a kernel eigenvalue problem. Neural Computation, 10(5):1299-1319, 1998.
26. C. Shen, J. Kim, L. Wang, and A. van den Hengel. Positive semidefinite metric learning with boosting. In NIPS. 2009.
27. M. Sugiyama. Dimensionality reduction of multimodal labeled data by local fisher discriminant analysis. JMLR, 8:1027-1061, 2007.
28. L. Torresani and K.-C. Lee. Large margin component analysis. In NIPS, 2006.
29. X.-J. Wang, L. Zhang, F. Jing, and W.-Y. Ma. Annosearch: Image auto-annotation by search. In CVPR, 2006.
30. K.Weinberger, J. Blitzer, and L. Saul. Distance metric learning for large margin nearest neighbor classification. In NIPS, 2006.
31. K. Weinberger and G. Tesauro. Metric learning for kernel regression. In Artificial Intelligence and Statistics, 2007.
32. L.Wu, S. C. H. Hoi, R. Jin, J. Zhu, and N. Yu. Distance metric learning from uncertain side information with application to automated photo tagging. In ACM Multimedia, 2009.
33. L. Wu, R. Jin, and A. K. Jain. Tag completion for image retrieval. PAMI, 35(3):716-727, 2013.
34. P. Wu, S. C.-H. Hoi, P. Zhao, and Y. He. Mining social images with distance metric learning for automated image tagging. In WSDM, 2011.
35. L. Yang and R. Jin. Distance metric learning: A comprehensive survey. Technical report, Michigan State Univ., 2009.