This also makes the method highly improbably as a model of how human beings recognize faces. The success of the algorithm depends largely on the generality of the training set used to generate the eigenfaces. The present algorithm cannot detect faces that are smaller than the average face. This problem can be solved by building pyramids for the eigenfaces and average face as well as the input. However, this greatly increases the number of calculations.
Performance is highly dependent on the aspect ratio of the faces in the input images.
In most cases, the use of DFFS improves performance but in some, it hinders performance. The choice of whether or not to use DFFS seems to be adhoc. This file detects faces in an input image.