Face Recognition Research

Research scholars have found face recognition as an important area for their work because our face is a combination of various features (facial features )like the eyes ,ears ,nose etc. Various research works have been also carried out in this area.
This paper focuses on a brief survey over the currently employed techniques of face recognition along with their advantages and disadvantages applications and constraints. Some of the most general methods include Eigenface (Eigenvectors or PCA), Neural Networks, Geometric Based Template Matching approaches etc. Further this paper performs an analysis on these face recognition approaches in order to constitute face representations .This survey also deals with the factors affecting the recognition

Accessories of 3D image deformation model can be identified in two ways in different screening environment. Model 1: A Model accessory confirms that the model can be based on the coefficient representing the shape and texture inherent in the face and independent of imaging conditions (Georghiades et al., 2001; Zhao and Chellappa, 2000). Currently, (Zhao and Chellappa, 2000) amalgamates 3D Morphable model with computer aided system. As a single image, the algorithm repeatedly calculates three- dimensional shape, texture and all relevant consideration of three-dimensional scene. Lambertian reflection is limited to lighting, specular reflections and shadows having a significant impact on the appearance of human skin that should not be considered into account. This method is based on three-dimensional facial deformation model to confine the exact properties of faces that can be routinely learned from the data set. Deformable model actually constitutes geometry and texture of the face and includes probability density function as face space. In recent development, in Bustard and Nixon (2010) uses ear identification as a biometric. Everyone has a unique ear pattern. In this paper, the author focuses on 3D Morphable model for head and ear. In (Shu-Fan and Shang-Hong, 2011) facial expressions are handled using the same approach of

CONCLUSION Although face recognition has been a challenging issue in the field of image processing and computer human interaction but due to its application in various fields it has received immense attention over the years. This survey dealt with a discussion over general time-line based face recognition techniques along with factors affecting them in different aspects as such as accuracy, performance etc. are discussed. It is also observed that to tackle different obstacles such as the pose variation, illumination conditions, facial aging etc. different techniques can be employed independent of each other. Moreover some integrated approaches have also been used to get over multiple face recognition factors in a single system. Thus, to handle all the obstacles of a face recognition an integrated system can be developed that contains the features of various face recognition and detection