Recognizing and Mask Removal in 3D Faces Even In Presence of Occlusions

ABSTRACT: 3D face recognition has the potential to achieve better accuracy than its 2D counterpart by measuring geometry of rigid features on the face. This avoids such pitfalls of 2D face recognition algorithms as change in lighting, different facial expressions, make-up and head orientation. Another approach is to use the 3D model to improve accuracy of traditional image based recognition by transforming the head into a known view. Then we consider 3D image for face recognition, Occlusions (extraneous objects that hinder face recognition e.g., scarf, glass, beard etc.,) are one of the greatest challenges in face recognition systems. We proposed our project under masked projection with high accuracy in face recognition system using classification algorithms. We propose a masked projection technique that can cope with missing data. Furthermore, we utilize a regional approach to improve the classification performance, where different regions serve as separate classifiers.