Models of face recognition and classification often adopt a framework in wh
ich faces are represented as points in a multidimensional space. This psych
ological face space organizes the faces according to similarity and makes p
redictions for representational theories of faces. A variety of image-proce
ssing techniques have been used to create novel stimuli in this space that
represent the average of a population or make a face appear more distinctiv
e. The current research examined the relation between the stimuli created b
y these image-processing techniques and the underlying psychological repres
entation as measured by multidimensional scaling (MDS) procedures. Morphing
procedures were used to create 16 faces that were embedded in a set of 84
other faces. Similarity ratings between all possible pairs of faces were co
llected, and the data were analyzed using MDS procedures. Dimensions that e
merged from the MDS solution included age, race, adiposity, and facial hair
. In the MDS space, the morphs appeared more typical than the parents, as p
redicted by the geometric model. A number of biases were examined including
the tendency of the morphs to be less typical than predicted, which may be
attributed to the effects of density near the center efface space. In addi
tion, age and facial-adiposity biases were found. The results support the u
se of the face-space framework for models of face recognition, although ima
ge-processing techniques that are designed to create novel stimuli in this
space may introduce systematic biases.