A Report on Multilinear PCA Plus GTDA to Deal With Face Image

1. Zong, W., G. B. Huang. Face Recognition Based on Extreme Learning Machine. – Neurocomputing, Vol. 74, 2011, No 16, pp. 2541-2556.10.1016/j.neucom.2010.12.041Search in Google Scholar

2. Liu, C., W. Xu, Q. Wu. TKPCA: Tensorial Kernel Principal Component Analysis for Action Recognition. – Mathematical Problems in Engineering, Article ID. 2013, pp. 816-836.10.1155/2013/816836Search in Google Scholar

3. Jolliffe, I. Principal Component Analysis. Wiley Online Library, 2005.10.1002/0470013192.bsa501Search in Google Scholar

4. Belhumeur, P. N., J. P. Hespanha, D. J. Kriegman. Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection. – IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 19, 1997, No 7, pp. 711-720.10.1109/34.598228Search in Google Scholar

5. Lu, H., K. N. Plataniotis, A. N. Venetsanopoulos. MPCA: Multilinear Principal Component Analysis of Tensor Objects. – IEEE Transactions on Neural Networks, Vol. 19, 2008, No 1, pp. 18-39.10.1109/TNN.2007.90127718269936Search in Google Scholar

6. Yan, S., D. Xu, Q. Yang, L. Zhang, X. Tang, H. J. Zhang. Multilinear Discriminant Analysis for Face Recognition. – IEEE Transactions on Image Processing, Vol. 16, 2007, No 1, pp. 212-220.10.1109/TIP.2006.88492917283779Search in Google Scholar

7. Tao, D., X. Li, X. Wu, S. Maybank. General Tensor Discriminant Analysis and Gabor Features for Gait Recognition. – IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 29, 2007, No 10, pp. 1700-1715.10.1109/TPAMI.2007.109617699917Search in Google Scholar

8. He, X., D. Cai, P. Niyogi. Tensor Subspace Analysis. A – In: Advances in Neural Information Processing Systems, 2005, pp. 499-506.Search in Google Scholar

9. Song, F., D. Zhang, D. Mei, Z. Guo. A Multiple Maximum Scatter Difference Discriminant Criterion for Facial Feature Extraction. – IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, Vol. 37, 2007, No 6, pp. 1599-1606.10.1109/TSMCB.2007.906579Search in Google Scholar

10. Wang, S. J., C. G. Zhou, X. Fu, Fusion Tensor Subspace Transformation Framework. – Plos One, Vol. 8, 2013, No 7.10.1371/journal.pone.0066647369809123840864Search in Google Scholar

11. Kong, S., D. Wang. A Report on Multilinear PCA Plus Multilinear LDA to Deal with Tensorial Data: Visual Classification as an Example. – arXiv Preprint, arXiv. 1203.0744v1, March 2012.Search in Google Scholar

12. Baboli, A. A. S., G. Rezai-Rad, A. S. Baboli. MPCA+DATER: A Novel Approach for Face Recognition Based on Tensor Objects. – In: 18th Telecommunications Forum, November 2010, pp. 123-12810.1109/ISTEL.2010.5734127Search in Google Scholar

13. Baboli, A. S., S. M. H. Nia, A. A. S. Baboli. A New Method Based on MDA to Enhance the Face Recognition Performance. – International Journal of Image Processing, Vol. 5, 2011, No 1, pp. 69-77.Search in Google Scholar

14. Hosseyninia, S. M., F. Roosta, A. A. S. Baboli. Gholamali. Improving the Performance of MPCA+MDA for Face Recognition. – In: 19th Iranian Conference on Electrical Engineering, 2011, pp. 14-19.Search in Google Scholar

15. Li, J., L. Zhang, D. Tao, H. Sun, Q. Zhao. A Prior Neurophysiologic Knowledge Free Tensor-Based Scheme for Single Trial EEG Classification. – In: IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol. 17, 2009, No 2, pp. 107-115.10.1109/TNSRE.2008.200839419273039Search in Google Scholar

16. Lu, H., K. N. Plataniotis, A. N. Venetsanopoulos. A Taxonomy of Emerging Multilinear Discriminant Analysis Solutions for Biometric Signal Recognition. – Biometrics: Theory, Methods, and Application, Wiley/IEEE, 2009, pp. 21-45.10.1002/9780470522356.ch2Search in Google Scholar

17. Kolda, T. G., B. W. Bader. Tensor Decompositions and Applications. – SIAM Review, Vol. 51, 2009, No 3, pp. 455-500.10.1137/07070111XSearch in Google Scholar

18. Phillips, P. J., H. Moon, S. A. Rizvi, P. Rauss. The FERET evaluation method for face recognition algorithms. – IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 22, 2000, No 10, pp. 1090-1104.10.1109/34.879790Search in Google Scholar

19. Tang, L. Super-Resolution Reconstruction Method Integrated With Image Registration. – International Information and Engineering Technology Association, Vo1. 2, 2015, No 1, pp. 29-32.10.18280/rces.020105Search in Google Scholar

20. Fan, Y. Semantic Annotation and Storagefor Tourism Information. – International Information and Engineering Technology Association, Vo1. 2, 2015, No 2, pp. 1-4.Search in Google Scholar

21. Bader, B., T. G. Kolda. Tensor Toolbox. Version 2.3. Sandia National Laboratories, Albuquerque, NM [Online]. Available. http://csmr.ca.sandia.gov/~tgkolda/TensorToolbox/Search in Google Scholar