The Effects of Blur and Inversion on the Recognition of Ambient Face Images/

When viewing unfamiliar faces that vary in expressions, angles, and image quality, observers make many recognition errors. Specifically, in unconstrained identity-sorting tasks, observers struggle to cope with variation across different images of the same person while succeeding at telling different people apart. The use of ambient face images in this simple card-sorting task reveals the magnitude of these face recognition errors and suggests a useful platform to reexamine the nature of face processing using naturalistic stimuli. In the present study, we chose to investigate the impact of two basic stimulus manipulations (image blur and face inversion) on identity sorting with ambient images. Although these manipulations are both known to affect face processing when well-controlled, frontally viewed face images are used, examining how they affect performance for ambient images is an important step toward linking the large body of research using controlled face images to more ecologically valid viewing conditions. Briefly, we observed a high cost of image blur regardless of blur magnitude, and a strong inversion effect that affected observers’ sensitivity to extrapersonal variability but did not affect the number of unique identities they estimated were present in the set of images presented to them.