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
No comments:
Post a Comment