Abstract
Faces convey very rich information that is critical for intact social interaction. To extract this information efficiently, faces should be easily detected from a complex visual scene. Here, we asked which features are critical for face detection. To answer this question, we presented non-face objects that generate a strong percept of a face (i.e., Pareidolia). One group of participants rated the faceness of this set of inanimate images. A second group rated the presence of a set of 12 local and global facial features. Regression analysis revealed that only the eyes or mouth significantly contributed to faceness scores. We further showed that removing eyes or mouth, but not teeth or ears, significantly reduced faceness scores. These findings show that face detection depends on specific facial features, the eyes and the mouth. This minimal information leads to over-generalization that generates false face percepts but assures that real faces are not missed.
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