Robust subspace segmentation by simultaneously learning data representations and their affinity matrix

IJCAI International Joint Conference on Artificial Intelligence

Volumn 2015-January, Issue , 2015, Pages 3547-3553

  Guo, Xiaojie ^a  

^a University of Chinese Academy of Sciences   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; CLUSTERING ALGORITHMS; CONSTRAINED OPTIMIZATION; LAGRANGE MULTIPLIERS; OPTIMIZATION;

AUGMENTED LAGRANGIANS; OPTIMAL SOLUTIONS; SPECTRAL CLUSTERING; STATE OF THE ART; SUB-SPACE SEGMENTATION; SYNTHETIC AND REAL DATA; UNIFIED OPTIMIZATION FRAMEWORK; UNION OF SUBSPACES;

MATRIX ALGEBRA;

EID: 84949883985     PISSN: 10450823     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (22)

1. P. Bradley and O. Mangasarian. K-plane clustering. Journal of Global Optimization, 16(1):23-32, 2000.
2. E. Candès, J. Romberg, and T. Tao. Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information. IEEE Transactions on Image Processing, 52(2):489-509, 2006.
3. D. Donoho. Compressed sensing. IEEE Transactions on Information Theory, 52(4):1289-1306, 2006.
4. E. Elhamifar and R. Vidal. Space subspace clustering. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pages 2790-2797, 2009.
5. J. Feng, Z. Lin, H. Xu, and S. Yan. Robust subspace segmentation with block-diagonal prior. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pages 3818-3825, 2014.
6. D. Graham and N. Allinson. Characterizing virtual eigensignatures for general purpose face recognition. In Face Recognition: From Theory to Applications; NATO ASI Series F, Computer and Systems Sciences, volume 163, pages 446-456, 1998.
7. J. Ho, M. Yang, J. Lim, K. Lee, and D. Kriegman. Clustering appearances of objects under varying illumination conditions. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pages 11-18, 2003.
8. W. Hong, J. Wright, K. Huang, and Y. Ma. Multiscale hybrid linear models for lossy image representation. IEEE Transactions on Image Processing, 15(12):3655-3671, 2006.
9. K. Lee, J. Ho, and D. Kriegman. Acquiring linear subspaces for face recognition under variable lighting. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(5):684-698, 2005.
10. Z. Lin, R. Liu, and Z. Su. Linearized alternating direction method with adaptive penalty for low rank representation. In Proceedings of Advances in Neural Information Processing Systems (NIPS), pages 612-620, 2011.
11. G. Liu, Z. Lin, S. Yan, J. Sun, Y. Yu, and Y. Ma. Robust recovery of subspace structures by low-rank representation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 34(1):171-184, 2013.
12. C. Lu, H. Min, Z. Zhao, L. Zhu, D. Huang, and S. Yan. Robust and efficient subspace segmentation via least squares regression. In Proceedings of European Conference on Computer Vision, pages 347-360, 2012.
13. C. Lu, J. Feng, Z. Lin, and S. Yan. Correlation adaptive subspace segmentation by trace lasso. In Proceedings of International Conference on Computer Vision, pages 1345-1352, 2013.
14. Y. Ma, H. Derksen, W. Hong, and J. Wright. Segmentation of multivariate mixed data via lossy coding and compression. IEEE Transactions on Pattern Analysis and Machine Intelligence, 29(9):1546-1562, 2007.
15. Y. Ma, A. Yang, H. Derksen, and R. Fossum. Estimation of subspace arrangements with applications in modeling and segmenting mixed data. SIAM Review, 50(3):413-458, 2008.
16. F. Nie, D. Xu, I. Tsang, and C. Zhang. Spectral enbedded clustering. In Proceedings of International Joint Conference on Artifical Intelligence, pages 1181-1186, 2009.
17. F. Nie, X. Wang, and H. Huang. Clustering and projected clustering with adaptive neighbors. In Proceedings of ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 977-986, 2014.
18. S. Rao, R. Tron, R. Vidal, and Y. Ma. Motion segmentation in the presence of outlying, incomplete, or corrupted trajectories. IEEE Transactions on Pattern Analysis and Machine Intelligence, 32(10):1832-1845, 2010.
19. B. Saha, D. Pham, D. Phung, and S. Venkatesh. Sparse subspace clustering via group sparse coding. In Proceedings of SIAM International Conference on Data Mining, pages 130-138, 2013.
20. J. Shi and J. Malik. Normalized cuts and image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(8):888-905, 2000.
21. R. Vidal, Y. Ma, and S. Sastry. Generalized principal component analysis (GPCA). IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(12):1-15, 2005.
22. R. Vidal. A tutorial on subspace clustering. IEEE Signal Processing Magzine, 28:52-68, 2010.