With the development of artificial intelligence and machine vision, face recognition has become a hot topic of pattern recognition.This paper describes the review-based comparison and recognition of challenges using holistic and hybrid appearance based approaches and the recent techniques used for improving recognition accuracy. The accuracy or efficiency of the techniques depends on the situation where the system is used. In addition, several major issues for further research in the area of face recognition are also pointed out for further improvement

1. A. Pentland et al. “ View - based and modular eigen space for face Recognition ”, In CVPR ’ 94, 1994.
2. A. Saradha and S. Annadurai ,“ A Hybrid feature extraction approach for face recognition systems” ICGST- GVIP journal, Volume(5), May 2005.
3. Rong-Hua Li, Eddie, C.L. Chan, George Baciu , “DLDA and LDA/QR Equivalence Framework for Human Face Recognition”, Proc. 9th IEEE Int. Conf. on Cognitive Informatics (ICCI’10), 978-1-4244-8040-1©2010 IEEE
4. Shiladitya Chowdhury, Jamuna Kanta Sing, Dipak kumar Basu and Mita Nasipuri, “Feature Extraction by Fusing Local and Global Discriminant Features: An Application to Face Recognition, Jadavpur University, 978-1-4244-5967-4/10/$26.00 ©2010 IEEE.
5. G.H. Huang, and H.H. Shao, “ Kernel Principal Component analysis and application in Face Recognition”Computer Engineering .J.Shanghai, vol. 30, no.13, pp.13-14, July.2004.
6. J. R. Solar, and P. Navarreto, “ Eigen space – based face recognition: A comparative study of different approaches ”, IEEE Transactions on Systems man And Cybernetics- part c:

PCA IPCA LDA SVM BPNN 2DRPCA BAYESIAN