Size Effects in the Recognition of Blurry Faces

Abstract

Spatial frequencies critical for recognition of faces are scale-dependent. Progressively coarser features of the face are utilized at smaller sizes, despite the availability of finer features. Blur removes fine details in an image, disrupting the finer features utilized for recognition at large sizes. At smaller sizes, observers utilize coarser features, and thus, recognition may be less impacted by blur. This coupling between size and critical spatial frequencies allows us to predict a regime in which observers tolerate blur better with decreasing image sizes within a range of moderate face sizes. We tested recognition of famous faces in four conditions: large-intact, small-intact, large-blurry, and small-blurry. Observers showed high recognition performance in both intact conditions. Blur significantly disrupted recognition, yet accuracy was significantly and consistently higher in the small-blurry compared to the large-blurry condition. These results are suggestive of an inherent scale-dependent mechanism that, at certain sizes, negatively impacts recognition of blurry images.