Real Time Face Recognition and Identification

1. Deshpande, N. T., and Ravishankar, S. Utilising the Viola-Jones algorithm and a PCA/ANN fusion, face detection and recognition.
1173–1189 in Advances in Computational Sciences and Technology, 10(5).
2. M. Manjeet Kaur Kavia, 2016. A paper on face recognition technologies survey. The sixth issue of the International Journal of
Scientific and Research Publications.
3. PCA Algorithm for Human Face Recognition by Ohol, M. R. M., & Ohol, M. S. R.4. Kim, T. H., Kasar, M. M., & Bhattacharyya (2016). Review of face recognition using neural networks. 10(3), 81–100, International
Journal of Security and Its Applications.
5. Samoylov, A., Minin, P., and A. Egorov (2014, November). Mikhaylov, D. Face Tracking and Detection from Image and Data
Collection.
6. Liu, Z., and Wang, Y. video face tracking and detection utilizing dynamic programming. 2000 Proceedings of the Image Processing
Conference. 2000 International Conference on, pp. 53–56 inVolume 1. IEEE.
7. IEEE, Bode, R., & M. J. Priyadarshini (2016). Face Tracking and Detection Using Viola Jones and KLT. Engineering and Applied
Sciences Journal of the ARPN, 11(23), 13472-1347
8. Pentland and M. Turk, Eigenfaces for recognition, Journal of Cognitive Neuroscience, 3(1),p. 7186, 1991.
9. H. Lu, K. N. Platanista’s, and A. N. Venetsanopoulos (2008), "MPCA: Multilinear Principal Component Analysis of Tensor
Objects," IEEE Trans. on Neural Networks, 19(1):1839.
10. A case for the average-half-face in 2D and 3D for face recognition, IEEE Computer Society,Hague’s, J., and Aggarwal, J.K.