  Template matching is one of the most prevalent pattern recognition methods
worldwide. It has found uses in most visual concept detection fields. In this
work, we investigate methods for improving template matching by adjusting the
weights of different regions of the template. We compare several weight maps
and test the methods using the FERET face test set in the context of human eye
detection.
