Open sorting tasks that include multiple face images of the same person require participants to make identity judgments in order to group images of the same person. When participants are unfamiliar with the identity, natural variation in the images due to changes in lighting, expression, pose, and age lead participants to divide images of the same person into different “identity” piles. Although this task is being increasingly used in current research to assess unfamiliar face perception, no previous work has examined whether there is systematicity across participants in how identity groups are composed. A cluster analysis was performed using two variations of the original face sorting task. Results identify groups of images that tend to be grouped across participants and even across changes in task format. These findings suggest that participants responded to similar signals such as tolerable change and similarity across images when ascribing identity to unfamiliar faces. / Graduate

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Natural variability can make different instances of the same face appear remarkably dissimilar. Such variability rarely affects familiar face recognition. However, small differences in appearance between encounters can have really detrimental effects on identifying instances of unfamiliar faces as the same person. In typical face processing research, within-person variability is experimentally controlled, in order to explore the influences of between-person variability in face processing directly. That is, face stimuli are constrained so that differences between individual faces are restricted to identity-specific information; shape and texture. To this end, it remains unclear whether such natural variability plays a part in normal face processing. In this thesis, a series of experiments explore whether experiencing natural variability is beneficial in normal face processing. Specifically, the experiments described within this thesis address whether there is a role of within-person variability in face learning, with various manipulations, and also whether it has a role in improving unfamiliar face matching. The results suggest that experiencing variability is important in face learning – specifically in developing stable face representations. It was also found to be beneficial in improving unfamiliar face matching. Additional manipulations, such as the presence of additional person information, did not show any additional benefit to face learning – unlike previous studies. I suggest that the differences between the results observed here and previous studies highlight differences in measures of familiarity, and the importance of considering what different measures tell us about face processing. I discuss these findings in relation to previous face learning studies, in addition to face perception methodologies overall. Put simply, I suggest that in order to understand face identification processes comprehensively, it is important to consider both between- and within-person variability.

Face recognition is widely held to rely on 'configural processing', recently defined as an analysis of metric distances between features. Given that face recognition concerns those faces of people who we know, it is suggested that our unique representations of familiar faces contain information about these metric distances. The experiments in this thesis examine the hypothesis that face recognition relies on 'configural processing' by comparing performance between familiar and unfamiliar faces in a range of tasks. Experiments in the first half of the thesis investigate the effects of geometric distortions on different face tasks. Experiments in the second half examine familiarity advantages in rescaling distorted facial images. The main findings are that face recognition might not rely on simple measures of metric distances between features, and that observers show a surprising degree of tolerance to configural changes applied to familiar faces. This suggests that an operationalisation of configural processing will need to consider other measures that do not survive the image deformations tested in this thesis. The findings are discussed in relation to existing research on familiar face recognition as distinct from unfamiliar face perception.

published_or_final_version / Dentistry / Master / Master of Dental Surgery

published_or_final_version / Dental Surgery / Master / Master of Dental Surgery

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