Paper Title
A Brief Survey on 2D and 3D Face Recognition

Abstract
The extensive use passwords and cards in biometric system, face recognition are having more advantages because of noncontact process. Face recognition can be consider one of the most commonly use and complex object recognition biometric system by human beings. Because face structures of human beings are almost similar. Besides, in reality world most of the face recognition cases only one image is available for training and many problems has arise when the images are acquired under uncontrolled situations such as illumination, pose variation, time delay, environment condition and occlusion. Very less amount of work has done in occlusions and age variation problems. In 3D face recognition it is intended to work on 3-Dimensional dataset representing face, illumination and head shape as range data or polygonal meshes. We can divide the 3D face recognition into three categories such as surface-based, statistical and model-based approaches. This paper provide a brief survey on 2D and 3D face recognition using linear subspace methods like PCA, LDA, ICA and Bayesian etc.,. this paper gives overview on the existing and most commonly used 2D and 3D face database. Keywords— Face recognition, PCA, LDA, ICA, Bayesian, Benchmark, 2D face database, 3D face database.