Open Access
Issue
MATEC Web of Conferences
Volume 44, 2016
2016 International Conference on Electronic, Information and Computer Engineering
Article Number 01039
Number of page(s) 4
Section Computer, Algorithm, Control and Application Engineering
DOI https://doi.org/10.1051/matecconf/20164401039
Published online 08 March 2016
  1. Jafri, R., Arabnia, H. R. A survey of face recognitiontechniques. Jips, 11 (19) (2009) 29–33
  2. Turk, M., Pentland, A, Eigenfaces for recognition. Journal of Cognitive Neuroscience, 3 (1) (2007) 71–86 [CrossRef]
  3. Belhumeur, P. N., Hespanha, J. P., Kriegman, D. J. Eigenfaces vs. fisherfaces: recognition using class specific linear projection. IEEE Trans. on Pattern Analysis and Machine Intelligence, 19 (7) (1997) 711–720 [CrossRef]
  4. Chien, J. T., Wu, C. C, Discriminant waveletfaces and nearest feature classifiers for face recognition. IEEE Trans. on Pattern Analysis and Machine Intelligence, 24 (12) (2002) 1644–1649 [CrossRef]
  5. Fidler, S., Sko aj, D., Leonardis, A. Combining reconstructive and discriminative subspace methods for robust classification and regression by subsampling. IEEE Trans. on Pattern Analysis and Machine Intelligence, 28 (3) (2006) 337–350 [CrossRef]
  6. J.Wright, A.Y.Yang, A.Ganesh, S.S. Sastry, Y. Ma, Robust face recognition via sparse representation, IEEE Trans. on Pattern Analysis and Machine Intelligence, 31 (2) (2009) 210–227 [CrossRef]
  7. B. Cheng, J. Yang, S. Yan, Y. Fu, and T. Huang. Learning with 11-graph for image analysis. IEEE Trans. Image Processing, 19 (4) (2010) 858–866 [CrossRef]
  8. S. Gao, I. Tsang, L. Chia, Kernel sparse representation for image classification and face recognition. In ECCV, 6314 (2010) 1–14
  9. M. Yang, L. Zhang. Gabor feature based sparse representation for face recognition with Gabor occlusion dictionary. In ECCV, 6316 (2010) 448–461.
  10. M. Yang, L. Zhang, J. Yang, D. Zhang. Robust sparse coding for face recognition. IEEE, 42 (7) (2011) 625–632
  11. Naseem, I., Togneri, R., Bennamoun, M. Linear regression for face recognition. IEEE Trans. on Pattern Analysis and Machine Intelligence, 32 (11) (2010) 2106–2112. [CrossRef]
  12. X. Luan, B. Fang, Face recognition with contiguous occlusion using linear regression and level set method. Neurocomputing, 122 (2013) 386–397 [CrossRef]
  13. X. Luan, B. Fang, Extracting sparse error of robust PCA for face recognition in the presence of varying illumination and occlusion. Pattern Recognition, 47 (2) (2014) 495–508 [CrossRef]
  14. L. Zhang, M. Yang, X. Feng, Sparse representation or collaborative representation: Which helps face recognition? Proceedings of the 2011 International Conference on Computer Vision IEEE Computer Society, (2011) 471–478
  15. A. Georghiades, P. Belhumeur, D. Kriegman, From few to many: Illumination cone models for face recognition under variable lighting and pose, IEEE Trans. on Pattern Analysis and Machine Intelligence, 23 (2001) 643–660 [CrossRef]
  16. A. Martinez, R. Benavente, The AR face database, CVC Tech. Report. 24, 1998.

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.