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Mathematical Problems in Engineering
Volume 2017, Article ID 4787039, 9 pages
https://doi.org/10.1155/2017/4787039
Research Article

Subspace Clustering with Sparsity and Grouping Effect

School of Mathematics and Statistics, Xidian University, Xi’an 710126, China

Correspondence should be addressed to Weiwei Wang; nc.ude.naidix.liam@gnawww

Received 6 December 2016; Accepted 6 March 2017; Published 22 March 2017

Academic Editor: Simone Bianco

Copyright © 2017 Binbin Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. L. Parsons, E. Haque, and H. Liu, “Subspace clustering for high dimensional data: a review,” SIGKDD Explorations, vol. 6, no. 1, pp. 90–105, 2004. View at Google Scholar
  2. 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, vol. 35, no. 1, pp. 171–184, 2013. View at Publisher · View at Google Scholar · View at Scopus
  3. K. Kanatani, “Motion segmentation by subspace separation and model selection,” in Proceedings of the 8th International Conference on Computer Vision, pp. 586–591, Vancouver, Canada, July 2001. View at Scopus
  4. B. Cheng, G. Liu, J. Wang, Z. Huang, and S. Yan, “Multi-task low-rank affinity pursuit for image segmentation,” in Proceedings of the IEEE International Conference on Computer Vision (ICCV '11), pp. 2439–2446, IEEE, Barcelona, Spain, November 2011. View at Publisher · View at Google Scholar · View at Scopus
  5. C. Zhang and R. R. Bitmead, “Subspace system identification for training-based MIMO channel estimation,” Automatica, vol. 41, no. 9, pp. 1623–1632, 2005. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  6. E. Elhamifar and R. Vidal, “Sparse subspace clustering,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, pp. 2790–2797, June 2009. View at Publisher · View at Google Scholar · View at Scopus
  7. E. Elhamifar and R. Vidal, “Sparse subspace clustering: algorithm, theory, and applications,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 35, no. 11, pp. 2765–2781, 2013. View at Publisher · View at Google Scholar · View at Scopus
  8. G. Liu, Z. Lin, and Y. Yu, “Robust subspace segmentation by low-rank representation,” in Proceedings of the 27th International Conference on Machine Learning (ICML '10), pp. 663–670, June 2010. View at Scopus
  9. 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 the IEEE 12th European Conference on Computer Vision, pp. 347–360, Florence, Italy, October 2012.
  10. C. Lu, J. Feng, Z. Lin, and S. Yan, “Correlation adaptive subspace segmentation by trace lasso,” in Proceedings of the 14th IEEE International Conference on Computer Vision (ICCV '13), pp. 1345–1352, IEEE, Sydney, Australia, December 2013. View at Publisher · View at Google Scholar · View at Scopus
  11. H. Hu, Z. Lin, J. Feng, and J. Zhou, “Smooth representation clustering,” in Proceedings of the 27th IEEE Conference on Computer Vision and Pattern Recognition (CVPR '14), pp. 3834–3841, Columbus, Ohio, USA, June 2014. View at Publisher · View at Google Scholar · View at Scopus
  12. D.-S. Pham, S. Budhaditya, D. Phung, and S. Venkatesh, “Improved subspace clustering via exploitation of spatial constraints,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR '12), pp. 550–557, June 2012. View at Publisher · View at Google Scholar · View at Scopus
  13. J. Shi and J. Malik, “Normalized cuts and image segmentation,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, no. 8, pp. 888–905, 2000. View at Publisher · View at Google Scholar · View at Scopus
  14. P. N. Belhumeur, J. P. Hespanha, and D. J. Kriegman, “Eigenfaces vs. fisherfaces: recognition using class specific linear projection,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 711–720, 1997. View at Publisher · View at Google Scholar · View at Scopus
  15. J. J. Hull, “A database for handwritten text recognition research,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 16, no. 5, pp. 550–554, 1994. View at Publisher · View at Google Scholar · View at Scopus
  16. X. Yuan and J. Yang, “Sparse and low-rank matrix decomposition via alternating direction methods,” Pacific Journal of Optimization, vol. 9, no. 1, 2009. View at Google Scholar
  17. Z. Lin, M. Chen, L. Wu, and Y. Ma, “The augmented lagrange multiplier method for exact recovery of corrupted low-rank matrices,” 2009.
  18. R. H. Bartels and G. W. Stewart, “Solution of the matrix equation AX + XB = C [F4],” Communications of the ACM, vol. 15, no. 9, pp. 820–826, 1972. View at Publisher · View at Google Scholar · View at Scopus
  19. P. Arbeláez, M. Maire, C. Fowlkes, and J. Malik, “Contour detection and hierarchical image segmentation,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 33, no. 5, pp. 898–916, 2011. View at Publisher · View at Google Scholar · View at Scopus
  20. W. M. Rand, “Objective criteria for the evaluation of clustering methods,” Journal of the American Statistical Association, vol. 66, no. 336, pp. 846–850, 1971. View at Publisher · View at Google Scholar · View at Scopus
  21. M. Meila, “Comparing clusterings: an axiomatic view,” in Proceedings of the 22nd International Conference on Machine Learning (ICML '05), pp. 577–584, Bonn, Germany, August 2005. View at Scopus
  22. D. Zhou, O. Bousquet, and T. Lal, “Learning with local and global consistency,” Advances in Neural Information Processing Systems, vol. 16, no. 16, pp. 321–328, 2004. View at Google Scholar
  23. G. Mori, X. Ren, A. A. Efros, and J. Malik, “Recovering human body configurations: combining segmentation and recognition,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '04), vol. 2, pp. II-326–II-333, usa, July 2004. View at Publisher · View at Google Scholar · View at Scopus