  Majority of the face recognition algorithms use query faces captured from
uncontrolled, in the wild, environment. Often caused by the cameras limited
capabilities, it is common for these captured facial images to be blurred or
low resolution. Super resolution algorithms are therefore crucial in improving
the resolution of such images especially when the image size is small requiring
enlargement. This paper aims to demonstrate the effect of one of the
state-of-the-art algorithms in the field of image super resolution. To
demonstrate the functionality of the algorithm, various before and after 3D
face alignment cases are provided using the images from the Labeled Faces in
the Wild (lfw). Resulting images are subject to testing on a closed set face
recognition protocol using unsupervised algorithms with high dimension
extracted features. The inclusion of super resolution algorithm resulted in
significant improved recognition rate over recently reported results obtained
from unsupervised algorithms.
