Automated Multi Face Identification
 |
International Journal of Computer & Organization Trends (IJCOT) |  |
| © 2017 by IJCOT Journal | ||
| Volume - 7 Issue - 5 |
||
| Year of Publication : 2017 | ||
| Authors : Kalpana Chauhan, Mrs.Mamta Yadav |
Citation
Kalpana Chauhan, Mrs.Mamta Yadav "Automated Multi Face Identification", International Journal of Computer & organization Trends (IJCOT), V7(5):5-7 Sep - Oct 2017, ISSN:2249-2593, www.ijcotjournal.org. Published by Seventh Sense Research Group.
Abstract
Face Identication is a fast growing and interesting area in real time application. Large Number of face identification have been developed in last decades. In this paper review of Automated Multiface Identification using many methods. Automated mutliface identification is Identifying the multi face by name. This review exmine all methods like it poses, facial expression and identify face. To identify any face we must have record the photo. We save photo in datebase.to identify we record that Generally contain name and photo. Multiface identification identify form multiface to one face that store in database.
References
[1] Issam Dagher, Incremental PCA-LDA algorithm?, International Journal of Biometrics and Bioinformatics (IJBB), Volume (4): Issue (2).
[2] J. Shermina,V. Vasudevan,An Efficient Face recognition System Based on Fusion of MPCA and LPP, American Journal of Scientific Research ISSN 1450-223X Issue 11(2010), pp.6-19.
[3] Ishwar S. Jadhav, V. T. Gaikwad, Gajanan U. Patil, Human Identification Using Face and Voice Recognition?, International Journal of Computer Science and Information Technologies, Vol. 2 (3), 2011.
[4] Yun-Hee Han,Keun-Chang Kwak, Face Recognition and Representation by Tensor-based MPCA Approach, 2010 The 3rd International Conference on Machine Vision (ICMV 2010).
[5] Neerja,Ekta Walia, Face Recognition Using Improved Fast PCA Algorithm, Proceedings of IEEE 2008.
[6] S.Sakthivel, Dr.R.Lakshmipathi, Enhancing Face Recognition using Improved Dimensionality Reduction and feature extraction Algorithms_An Evaluation with ORL database, International Journal of Engineering Science and Technology Vol. 2(6), 2010.
[7]Lin Luo, M.N.S. Swamy, Eugene I. Plotkin, ?A Modified PCA algorithm for face recognition, Proceedings of IEEE 2003.
[8] A. Hossein Sahoolizadeh, B. Zargham Heidari, and C. Hamid Dehghani, A New Face Recognition Method using PCA, LDA and Neural Network, International Journal of Electrical and Electronics Engineering 2:8 2008.
[9]Feroz Ahmed Siddiky, Mohammed Shamsul Alam,Tanveer Ahsan and Mohammed Saifur Rahim, An Efficient Approach to Rotation Invariant Face detection using PCA,Generalized Regression Neural network and Mahalanobis Distance by reducing Search space, Proceedings Of IEEE 2007.
[10] Vapnik. Statistical Learning Theory. JohnWiley and Sons, New York, 1998.
[11] E. Osuna, R. Freund, and F. Girosit. Training support vector machines: an application to face detection. Proc. of CVPR, pages 130–136, 1997.
[12] B. Heisele, T. Serre, and T. Poggio. A component based framework for face detection and identification. IJCV, 74(2):167–181, 2007.
[13] Q. Tao, D. Chu, and J. Wang. Recursive support vector machines for dimensionality reduction. IEEE Trans. NN, 19(1):189–193, 2008.
[14] Marian Stewart Bartlett, Javier R. Movellan, Terrence J. Sejonowski, ?Face Recognition by Independent Component Analysis, IEEE Transactions on Neural Networks, vol-13, No- 6,November 2002, PP 1450- 1464.
[15] Pong C.Yuen, J.H.Lai, ?Face representation using independent component analysis, Pattern Recognition 35 (2002) 1247-1257.
[16] Tae-Kyun Kim, Hyunwoo Kim, Wonjum Hwang, Josef Kittler, ?Independent component analysis in a local facial residue space for face recognition, Pattern Recognition 37 (2004) 1873-1885.
Keywords
Multiface identification identify form multiface to one face that store in database.