Psychological research on human faces has consistently shown that averageness strongly predicts attractiveness. The more faces are digitally morphed together — and more pronounced facial features fade away — the more attractive they become.
But an international team of researchers has discovered the “beauty-in-averageness” effect can be disrupted when a digitally morphed face is recognizable despite being a composite of multiple photographs. These “slightly-off” faces are viewed as less attractive compared to the original faces from which they were generated.
“The results provide a major qualification of the beauty-in-averageness effect, showing that the very same face blends can be either more or less attractive than the constituent faces depending on whether the constituents are identifiable,” lead researcher Jamin Halberstadt of the University of Otago wrote in the study, published in the November 2013 issue of Psychological Science.
For their study, Halberstadt and his colleagues digitally blended the faces of 28 famous Dutch persons and 28 famous New Zealanders. These celebrities — which included television, sports, and political personalities — were well known in their home country but virtually unknown to foreigners.
The resulting 14 Dutch and 14 New Zealander morphs were shown to nearly 120 students from the Netherlands and New Zealand, who rated the attractiveness of each face.
The students rated the unrecognizable morphed faces as more attractive than the original individual faces, and rated recognizable morphed faces as less attractive than the original individual faces.
Dutch students rated morphs of New Zealand celebrities as more attractive, but rated morphs of Dutch celebrities as less attractive. New Zealand students, on the other hand, rated morphs of Dutch celebrities as more attractive, but rated morphs of New Zealand celebrities as less attractive.
“A critical factor in studies showing dislike for distorted stimuli is that participants know what the stimuli are distortions of. In contrast, in studies of the beauty-in-averageness effect, the original faces are generally not known or not recognizable in the blend, which precludes any classification disfluency,” the researchers explained in their study.
The study was co-authored by Diane Pecher, René Zeelenberg, Laurent Ip Wai, and Piotr Winkielman.
