Transfer sparse coding for robust image representation

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2013, Pages 407-414

  Long, Mingsheng ^a,b   Ding, Guiguang ^b   Wang, Jianmin ^b   Sun, Jiaguang ^b   Guo, Yuchen ^b   Yu, Philip S ^c  

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

^b TSINGHUA UNIVERSITY   (China)

^c University of Illinois at Chicago   (United States)

Author keywords

image representation; sparse coding; transfer learning

Indexed keywords

CLASSIFICATION PERFORMANCE; DIFFERENT DISTRIBUTIONS; IMAGE REPRESENTATIONS; SPARSE CODING; SPARSE REPRESENTATION; STATE-OF-THE-ART METHODS; STATE-OF-THE-ART PERFORMANCE; TRANSFER LEARNING;

PATTERN RECOGNITION;

IMAGE CODING;

EID: 84887338420     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2013.59     Document Type: Conference Paper

References (24)

1. M. Aharon, M. Elad, A. Bruckstein, and Y. Katz. K-svd: An algorithm for designing overcomplete dictionaries for sparse representation. IEEE Transactions on Signal Processing, 54(11), 2006. 2, 4
2. M. Belkin and P. Niyogi. Laplacian eigenmaps and spectral techniques for embedding and clustering. In Advances in Neural Information Processing Systems 15, NIPS, 2001. 2
3. D. Cai, X. He, and J. Han. Spectral regression: A unified approach for sparse subspace learning. In Proceedings of the 7th IEEE International Conference on Data Mining, ICDM, 2007. 5
4. D. Cai, X. He, J. Han, and T. S. Huang. Graph regularized nonnegative matrix factorization for data representation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(8):1548-1560, 2011. 5
5. R. Fletcher. Practical methods of optimization. Wiley-Interscience, 1987. 4
6. S. Gao, I. W.-H. Tsang, L.-T. Chia, and P. Zhao. Local features are not lonely-laplacian sparse coding for image classification. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2010. 1, 2, 3
7. A. Gretton, K. M. Borgwardt, M. J. Rasch, B. Scholkopf, and A. J. Smola. A kernel method for the two-sample problem. In Advances in Neural Information Processing Systems 20, NIPS, 2006. 2, 3
8. K. Huang and S. Aviyente. Sparse representation for signal classification. In Advances in Neural Information Processing Systems 21, NIPS, 2007. 1
9. H. Lee, A. Battle, R. Raina, and A. Y. Ng. Efficient sparse coding algorithms. In Advances in Neural Information Processing Systems 20, NIPS, 2006. 1, 2, 3, 4, 5, 6
10. Y. N. Liu, F. Wu, Z. H. Zhang, Y. T. Zhuang, and S. C. Yan. Sparse representation using nonnegative curds and whey. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2010. 1, 2
11. J. Mairal, F. Bach, J. Ponce, and G. Sapiro. Online dictionary learning for sparse coding. In Proceedings of the International Conference on Machine Learning, ICML, 2009. 1, 2, 3, 4, 5
12. J. Mairal, F. Bach, J. Ponce, G. Sapiro, and A. Zisserman. Supervised dictionary learning. In Advances in Neural Information Processing Systems 23, NIPS, 2009. 1
13. S. J. Pan, J. T. Kwok, and Q. Yang. Transfer learning via dimensionality reduction. In Proceedings of the 22nd AAAI Conference on Artificial Intelligence, AAAI, 2008. 1, 3
14. S. J. Pan, I. W. Tsang, J. T. Kwok, and Q. Yang. Domain adaptation via transfer component analysis. IEEE Transactions on Neural Networks, 22(2):199-210, 2011. 1, 3, 6
15. S. J. Pan and Q. Yang. A survey on transfer learning. IEEE Transactions on Knowledge and Data Engineering, 22:1345-1359, 2010. 1, 2
16. B. Quanz, J. Huan, and M. Mishra. Knowledge transfer with low-quality data: A feature extraction issue. In Proceedings of the IEEE International Conference on Data Engineering, ICDE, 2011. 1, 2, 6
17. B. Quanz, J. Huan, and M. Mishra. Knowledge transfer with low-quality data: A feature extraction issue. IEEE Transactions on Knowledge and Data Engineering, 24(10), 2012. 1, 2, 6
18. A. Vedaldi and B. Fulkerson. VLFeat: An open and portable library of computer vision algorithms. http://www. vlfeat. org/, 2008. 5
19. C. Wang, D. Blei, and L. Fei-Fei. Simultaneous image classification and annotation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2009. 5
20. J. J. Wang, J. C. Yang, K. Yu, F. J. Lv, T. Huang, and Y. H. Gong. Localityconstrained linear coding for image classification. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2010. 1, 2
21. J. Wright, A. Yang, A. Ganesh, S. Sastry, and Y. Ma. Robust face recognition via sparse representation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 31(2), 2009. 1
22. J. Yang, K. Yu, Y. Gong, and T. Huang. Linear spatial pyramid matching using sparse coding for image classification. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2009. 1
23. M. Yang, L. Zhang, J. Yang, and D. Zhang. Robust sparse coding for face recognition. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2011. 1
24. M. Zheng, J. Bu, C. Chen, C. Wang, L. Zhang, G. Qiu, and D. Cai. Graph regularized sparse coding for image representation. IEEE Transactions on Image Processing, 20(5), 2011. 1, 2, 3, 4, 5, 6