Face pose estimation using PCA

Face recognition has been one among the foremost attention-grabbing and vital analysis fields within the past 20 years. The explanations come back from the necessity of automatic recognitions and police work systems, the interest in human sensory system on face recognition, and also the style of human-computer interface, etc. These researches involve information and researchers from disciplines like neurobiology, psychology, laptop vision, pattern recognition, image process, and machine learning, etc. Different techniques like principal component analysis (PCA), 2PCA, kernel principal component analysis (KPCA) are used for recognition. Distinction factors like illumination, pose, and expression are degrading the accuracy of recognition. In this paper we have taken 11 poses of a given subject before recognition and performed pose estimation for identifying correct pose of image, hence increasing the accuracy of recognition of image.