We describe the design of a component based face detector for gray scale images. We show that including parts of the face into the negative training sets of the component classifiers leads to improved system performance. We also introduce a method of using pairwise position statistics between component locations to more accurately locate the parts of a face. Finally, we illustrate an application of this technology in the creation of an accurate eye detection system.