Integrating GWTM and BAT algorithm for face recognition in low-resolution images

References

• Wei, C.-P., Chen, C.-F. and Frank Wang, Y.-C. Robust face recognition with structurally incoherent low-rank matrix decomposition. IEEE Trans. Image Process., 2014, 23, (8), 3294–3307. doi: 10.1109/TIP.2014.2329451
   PubMed Web of Science ®Google Scholar
• Zhao, W., Chellappa, R., Phillips, P. and Rosenfeld, A. Face recognition: a literature survey. ACM Comput. Surveys, 2003, 35, (4), 399–458. doi: 10.1145/954339.954342
   Web of Science ®Google Scholar
• Lu, Z. and Zhang, L. Face recognition algorithm based on discriminative dictionary learning and sparse representation. Neurocomputing, 2016, 174, 749–755. doi: 10.1016/j.neucom.2015.09.091
   Web of Science ®Google Scholar
• Xu, Y., Yang, J. and Jin, Z. A novel method for fisher discriminant analysis. IEEE Trans. Pattern Recogn., 2004, 37, (2), 381–384. doi: 10.1016/S0031-3203(03)00232-2
   Web of Science ®Google Scholar
• Turk, M. and Pentland, A. Face recognition using eigen faces. Proc. of IEEE Computer Society Conf. on computer vision and pattern recognition, 1991, pp. 586–591.
   Google Scholar
• Belhumeur, P. N., Hespanha, J. P. and Kriegman, D. J. Eigen faces vs. fisher faces: recognition using class specific linear projection. IEEE Trans. Pattern Anal. Mach. Intell., 1997, 19, (7), 711–720. doi: 10.1109/34.598228
   Web of Science ®Google Scholar
• He, X., Yan, S., Hu, Y., Niyogi, P. and Zhang, H. Face recognition using Laplacian faces. IEEE Trans. Pattern Anal. Mach. Intell., 2005, 27, (3), 328–340. doi: 10.1109/TPAMI.2005.55
   PubMed Web of Science ®Google Scholar
• Wright, J., Yang, A. Y., Ganesh, A., Sastry, S.S., Yi Ma, S.S. Robust face recognition via sparse representation. IEEE Trans. Pattern Anal. Mach. Intell., 2009, 31, 210–227. doi: 10.1109/TPAMI.2008.79
   PubMed Web of Science ®Google Scholar
• Yang, J., Zhang, D., Frangi, A. F. and Yang, J. Y. Two-dimensional PCA: a new approach to appearance-based face representation and recognition. IEEE Trans. Pattern Anal. Mach. Intell., 2004, 26, 131–137. doi: 10.1109/TPAMI.2004.1261097
   PubMed Web of Science ®Google Scholar
• Sugiyama, M. Local Fisher discriminant analysis for supervised dimensionality reduction. Proc. Int. Conf. Mach. Learn., 2006, 13, 905–912.
   Google Scholar
• Xu, Y. and Zhang, D. Represent and fuse bimodal biometric images at the feature level: complex-matrix-based fusion scheme. Opt. Eng., 2010, 49, (3).
   Web of Science ®Google Scholar
• Park, S. W. and Savvides, M. A multifactor extension of linear discriminant analysis for face recognition under varying pose and illumination. Adv. Signal Process., 2010, DOI:10.1155/2010/158395.
   Google Scholar
• Cover, T. and Hart, P. Nearest neighbor pattern classification. IEEE Trans. Inf. Theory, 1967, 13, 21–27. doi: 10.1109/TIT.1967.1053964
   Web of Science ®Google Scholar
• Baker, S. and Kanade, T. Hallucinating faces. Proc. IEEE Int. Conf. on automatic face and gesture recognition, 2000, pp. 83–88.
   Google Scholar
• Jian, M. and Lam, K.-M. Simultaneous hallucination and recognition of low-resolution faces based on singular value decomposition. IEEE Trans. Circuits Syst. Video Technol., 2015, 25, (11), 1761–1772. doi: 10.1109/TCSVT.2015.2400772
   Web of Science ®Google Scholar
• Zhua, N., Xua, T., Weia, L. and Tanga, T. A nearest neighbor classifier based on virtual test samples for face recognition. Light Electron Opt., 2015, 126, (21), 2799–2803. doi: 10.1016/j.ijleo.2015.07.014
   Web of Science ®Google Scholar
• Wen, X. and Wen, J. Improved the minimum squared error algorithm for face recognition by integrating original face images and the mirror images. Light Electron Opt., 2016, 127, (2), 883–889. doi: 10.1016/j.ijleo.2015.10.182
   Web of Science ®Google Scholar
• Soldera, J. Behaine, C. A. R. and Scharcanski, J. Customized orthogonal locality preserving projections with soft-margin maximization for face recognition. IEEE Trans. Instrum. Meas., 2015, 64, (9), 2417–2426. doi: 10.1109/TIM.2015.2415012
   Web of Science ®Google Scholar
• Lei, Y.-K. and Han, H. Discriminant sparse local spline embedding (D-SLSE) with application to face recognition. Knowl. Based Syst., 2015, 1–9. doi: 10.1016/j.knosys.2014.11.019
   Web of Science ®Google Scholar
• Lu, J. and Wang, G. Joint feature learning for face recognition. IEEE Trans. Inf. Foren. Sec., 2015, 10, (7), 1371–1383. doi: 10.1109/TIFS.2015.2408431
   Web of Science ®Google Scholar
• Chai, Z., Sun, Z. and Tan, T. Gabor ordinal measures for face recognition. IEEE Trans. Inf. Foren. Sec., 2014, 9, (1), 14–26. doi: 10.1109/TIFS.2013.2290064
   Web of Science ®Google Scholar
• Hennings-Yeomans, P. H., Baker, S. and Kumar, B. V. K. V. Recognition of low-resolution faces using multiple still images and multiple cameras. Proc. Int. Conf. on biometrics, 2008, pp. 1–6.
   Google Scholar
• Patil, N. K., Vasudha, S. and Boregowda, L. R. Performance improvement of face recognition system by decomposition of local features using discrete wavelet transforms. Electron. Syst. Des., 2013, 2, (11), 172–176.
   Google Scholar
• Rahman, M. T. and Bhuiyan, M. A. Face recognition using Gabor filters. Proc. Int. Conf. on computer and information technology, 2008, pp. 510–515.
   Google Scholar
• Su, Y., Shan, S., Chen, X. and Gao, W. Hierarchical ensemble of global and local classifiers for face recognition. IEEE Trans. Image Process., 2009, 18, (8), 1885–1896. doi: 10.1109/TIP.2009.2021737
   PubMed Web of Science ®Google Scholar
• Suruliandi, A., Meena, K. and Reena Rose, R. Local binary pattern and its derivatives for face recognition. IET Comput. Vision., 2012, 6, (5), 480–488. doi: 10.1049/iet-cvi.2011.0228
   Web of Science ®Google Scholar
• CVL face database from http://www.lrv.fri.uni-lj.si/facedb.html.
   Google Scholar
• Chai, Z., Sun, Z., Mendez-Vazquez H., He, R. and Tan, T. Gabor ordinal measures for face recognition. Biometrics Compend., 2014, 9, (1), 14–26.
   Google Scholar