FACE RECOGNITION ACROSS NON-UNIFORM MOTION BLUR, ILLUMINATION, AND POSE

FACE RECOGNITION FROM  BLUR, ILLUMINATION, AND POSE

             Existing methods for performing face recognition in the presence of blur are based on the convolution model and cannot handle non-uniform blurring situations that frequently arise from tilts and rotations in hand-held cameras. In this paper, we propose a methodology for face recognition in the presence of space-varying motion blur comprising of arbitrarily-shaped kernels. We model the blurred face as a convex combination of geometrically transformed instances of the focused gallery face, and show that the set of all images obtained by non-uniformly blurring a given image forms a convex set.

Fig:The gallery images ,illumination, facial expressions changes,small occlusions and differences in pose 

FOR LATEST IEEE PROJECTS  

                                                                                       CLICK HERE