Gender, average heads and categorical perception

Background: Our visual system uses a sophisticated mechanism called categorical perception to discriminate between highly similar objects. Small perceptual differences are enhanced thus creating clear boundaries between groups of items. Purpose: Although it seems to be an easy task to classify people by gender, we wondered whether facial information was sufficient for this purpose. Using the morphing technique of Blanz and Vetter (1999) we built an average three-dimensional head model from a database of 200 laser-scanned faces. We constructed an artificial gender continuum of this average head and used the faces in categorization and discrimination experiments. Results: Gender information was present in our face set and was easily identified by the participants. However when we tested for the existence of a categorical effect, we found no evidence of enhanced discrimination for faces straddling the gender category boundary. In previous studies we found also no evidence of categorical perception when using faces of individuals (Buelthoff & Newell, 2000). Our results with average faces confirm the previous findings and avoid any personal distinctive features that might interfere with the analysis. Furthermore, the use of average faces insures to have endpoint faces situated at approximately equal distance from the gender boundary. Conclusion: The absence of a categorical effect is surprising. Categorical perception has been shown repeatedly for other information displayed by faces (expressions and identity). Although we can tell quite reliably the sex of a face, there is no evidence of a distorted perceptual space for face gender. Furthermore our results show that categorical perception does not always exist when similar items are categorized, not even for an important category like faces. Clearly, despite its enormous importance for social interactions we have not learned to deal with the gender of faces very effectively.