Abstract
The new trend used in face recognition is 3D model, which predicates to provide more preciseness. The face geometry is changed drastically as the result of face expressions conceding in poor output of the procedure. Accordingly we initiate a method entitled Eigen faces, which are a set of eigenvectors, From the Possible Human Faces the respective Covariance matrix of the probability distribution of the High dimensional vector space is calculated, from which the set of eigenvectors are calculated. It is very precise in orientation and effectual for managing facial deformations. For higher efficacy, the face will be projected in 3D stereoscopy using disparity maps. This technique can be engaged in real time applications such as web cameras, mobile phones and digital cameras.
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