Delong Zhang¹, Min Zhang² and Yongbo Liu This email address is being protected from spambots. You need JavaScript enabled to view it.³

¹School of Electric Automation, Weifang University of Science and Technology, Weifang 262700, P.R. China
²Department of Mechanical and Electronic Engineering, Shandong Management University, Ji’nan 250357, P.R. China
³Department of City Management, Hunan City University, Yiyang, Hunan 413000, P.R. China

REFERENCES

1. [1] Ahonen, T., A. Hadid, and M. Pietikainen (2006) Face description with local binary patterns: Application to face recognition, IEEE Trans. Pattern Anal. Mach. Intell. 28(12), 20372041. doi: 10.1109/TPAMI.2006. 244
2. [2] Choi,J.Y.,W.D.Neve,K.N.Plataniotis,andY.M.Ro (2011) Collaborative face recognition for improved faceannotationinpersonal photo collectionsshared on online social networks, IEEE Trans. Multimedia 13(1), 1428. doi: 10.1109/TMM.2010.2087320
3. [3] Sun, Y., Y. Chen, X. Wang, and X. Tang (2014) Deep learning face representation by joint identificationverification, Proc.Adv.NeuralInf.Process.Syst. 1988 1996.
4. [4] Arashloo, S. R., and J. Kittler (2014) Dynamic texture recognition using multiscale binarised statistical image features, IEEE Trans. Multimedia 16(8), 20992109. doi: 10.1109/TMM.2014.2362855
5. [5] Ding, C., C. Xu, and D. Tao (2015) Multi-taskpose-invariant face recognition, IEEE Trans. Image Process 24(3), 980993. doi: 10.1109/TIP.2015.2390959
6. [6] Hsieh, C. K., S. H. Lai, and Y. C. Chen (2009) Expression-invariant face recognition with constrained optical flow warping, IEEE Trans. Multimedia 11(4), 600 610. doi: 10.1109/TMM.2009.2017606
7. [7] Paysan, P., R. Knothe, B. Amberg, S. Romdhani, and T. Vetter (2009) A 3D face model for pose and illumination invariant face recognition, Proc. IEEE Int. Conf. Adv. Video Signal Based Surveillance, 296301. doi: 10.1109/AVSS.2009.58
8. [8] Li, K. S., K. Li, and W. S. Zhang (2014) PCAface recognition algorithm based on improved BP neural network,ComputerApplicationsandSoftware 31(1),158 161.
9. [9] Wu, D. (2015) Multiple Information Fusion Face Recognition Research Based on Key Feature Points, Harbin: Harbin University of Science and Technology.
10. [10] Imtiaz, H., and S. A. Fattah (2012) A curvelet domain face recognition scheme based on local dominant feature extraction, ISRN Signal Process 12, 113. doi: 10.5402/2012/386505
11. [11] Luan, F., L. Lin, and Y. Wang (2010) 4-step face authentication algorithm based on SVM, 2010 Third Int. Symp. Intell. Inf. Technol. Secure. Informatics 1(2), 534538. doi: 10.1109/IITSI.2010.99
12. [12] Veerabhadrappa, L. Rangarajan (2010) Diagonal locality preserving projection as dimensionality reduction technique with application to face recognition, Image (Rochester N.Y.), 135140.
13. [13] Nair, A. R., B. C. Pilla, and E. George (2014) Multi feature face identification using hash table & binary tree classifier, International Journal of Advance Research in Computer Science and Management Studies 261272.
14. [14] Huang, H., H. Liu, and G. Liu (2012) Face recognition using pyramid histogram of oriented gradients and SVM, Int. J. Adv. Inf. Sci. Serv. Sci. 4(18), 18. doi: 10.4156/aiss.vol4.issue18.1
15. [15] Lei, Y. J., B. Mohammed, and A. E. S. Amar (2013) An efficient 3D face recognition approach based on the fusion of novel local low-level features, Pattern Recognition 46(1), 2437. doi: 10.1016/j.patcog.2012. 06.023
16. [16] Zeng, X. H., and X. W. Li (2014) Improving face recognition with linear discriminant regression classification based on fisher criterion, Computer Applications and Software 31(9), 184186.
17. [17] Li, Y. A., Y. J. Shen, G. D. Zhang, T. H. Yuan, X. J. Xiao, and H. L. Xu (2010) An efficient 3D face recognition method using geometric features, IEEE 2nd International Workshop on Intelligent Systems and Applications (ISA), 14. doi: 10.1109/IWISA.2010. 5473292
18. [18] Yashar, T., H. Ghassemian, and N. M. Mohammad (2012) 3D face recognition method using 2DPCA-Euclidean distance classification, ACEEE International Journal on Control System and Instrumentation 3(1), 15.
19. [19] Lei, Y., M. Bennamoun, M. Hayat, and Y. Guo (2014)
    An efficient 3D face recognition approach using local geometrical signatures, Pattern Recognition 46(2), 509 524. doi: 10.1016/j.patcog.2013.07.018
20. [20] Zhao, X., E. Dellandrea, L. Chen, and I. Kakadiaris (2011) Accurate land-marking of three-dimensional facial data in the presence of facial expressions and occlusions using a three-dimensional statistical facial feature model, IEEE Transactions on Systems Man and Cybernetics Part B: Cybernetics 41(5), 14171428. doi: 10.1109/TSMCB.2011.2148711
21. [21] Jin, Y., Y. Z. Wang, Q. Q. Ruan, and X. Q. Wang (2011) Anew schemefor 3D face recognition based on 2D gabor wavelet transform plus LBP, International Conference on Computer Science & Education, 860 865. doi: 10.1109/ICCSE.2011.6028773
22. [22] Torkhani, G., A. Ladgham, A. Sakly, and M. N. Mansouri (2017) A 3D–2D face recognition method based on extended gabor wavelet combining curvature and edge detection, Signal Image & Video Processing 11(5), 18. doi: 10.1007/s11760-016-1046-7
23. [23] Vinay, A., V. S. Shekhar, K. N. Balasubramanya Murthy, and S. Natarajan (2015) Face recognition using gabor wavelet features with PCAand KPCA- a comparative study,” Procedia Computer Science 57, 650 659. doi: 10.1016/j.procs.2015.07.434
24. [24] Kar, A., D. Bhattacharjee, D. K. Basu, M. Nasipuri, and M. Kundu (2013) Human face recognition using gabor based kernel entropy component analysis, International Journal of Computer Vision and Image Processing 2(3), 167174.