A face detector has to tell whether an image of arbitrary size contains a human face and if so, where
it is. One natural framework for considering this problem is that of binary classification, in which
a classifier is constructed to minimize the misclassification risk. Since no objective distribution can
describe the actual prior probability for a given image to have a face, the algorithm must minimize
both the false negative and false positive rates in order to achieve an acceptable performance