A Pose Recovery Algorithm to Minimize the Effects of Pose Variation on the Matching Performance of Elastic Bunch Graph Based Multiview Face Recognition System

Multiview face recognition is a challenging task of deformable pattern recognition. Machine recognition of human from his/her facial images available at any pose, intensity and expression is the ultimate goal of multiview face recognition system. In the present work the effect of variation of poses on the overall performance of face recognition engine based on elastic bunch graph matching technique is studied using K-means clustering algorithm. A geometry-based pose recovery algorithm is proposed to improve the performance of the system