The own-group bias in face recognition (OGB) is the greater facility to distinguish and recognize people from one's own group at the expense of people from other-groups. The OGB has been studied for many years, however, very little research focuses on finding a way to decrease or eliminate it, through training. Reporting five studies involving memory or matching tasks, the aim of the present thesis was to develop and to explore to what extent training can decrease or remove the OGB. French White participants, and South African White, Black and Coloured participants took part in different studies, using Black and White faces as stimuli. In each study, White participants from both countries presented the expected OGB prior to any intervention. However, the presence of the OGB in South African Black participants was detected only in one (matching task) study, instead recording a higher discrimination performance by Black participants for White faces in the other studies. As expected, South African Coloured participants did not display increased discrimination performance for any of the other stimuli groups, both being out-group stimuli. Results from the training studies revealed either (a) no effect of a distributed training in feature focus over 5 weeks; (b) an increase of the OGB after a focus on critical facial features; (c) a decrease of the OGB in a task-specific training using pictures whose quality had been manipulated, and; (d) an important implication of the presence/absence of the target in a field detection study. With some promising results, the present work contributes to our understanding of how training could be used to improve face-recognition, and especially other-group face recognition.

Eyewitness recognition is acknowledged to be prone to error but there is less understanding of difficulty in discriminating unfamiliar faces. This thesis examined the effects of face perception on identification of facial composites, and on unfamiliar face image comparison. Facial composites depict face memories by reconstructing features and configurations to form a likeness. They are generally reconstructed from an unfamiliar face memory, and will be unavoidably flawed. Identification will require perception of any accurate features, by someone who is familiar with the suspect and performance is typically poor. In typical face perception, face images are processed efficiently as complete units of information. Chapter 2 explored the possibility that holistic processing of inaccurate composite configurations will impair identification of individual features. Composites were split below the eyes and misaligned to impair holistic analysis (cf. Young, Hellawell, & Jay, 1987); identification was significantly enhanced, indicating that perceptual expertise with inaccurate configurations exerts powerful effects that can be reduced by enabling featural analysis. Facial composite recognition is difficult, which means that perception and judgement will be influence by an affective recognition bias: smiles enhance perceived familiarity, while negative expressions produce the opposite effect. In applied use, facial composites are generally produced from unpleasant memories and will convey negative expression; affective bias will, therefore, be important for facial composite recognition. Chapter 3 explored the effect of positive expression on composite identification: composite expressions were enhanced, and positive affect significantly increased identification. Affective quality rather than expression strength mediated the effect, with subtle manipulations being very effective. Facial image comparison (FIC) involves discrimination of two or more face images. Accuracy in unfamiliar face matching is typically in the region of 70%, and as discrimination is difficult, may be influenced by affective bias. Chapter 4 explored the smiling face effect in unfamiliar face matching. When multiple items were compared, positive affect did not enhance performance and false positive identification increased. With a delayed matching procedure, identification was not enhanced but in contrast to face recognition and simultaneous matching, positive affect improved rejection of foil images. Distinctive faces are easier to discriminate. Chapter 5 evaluated a systematic caricature transformation as a means to increase distinctiveness and enhance discrimination of unfamiliar faces. Identification of matching face images did not improve, but successful rejection of non-matching items was significantly enhanced. Chapter 6 used face matching to explore the basis of own race bias in face perception. Other race faces were manipulated to show own race facial variation, and own race faces to show African American facial variation. When multiple face images were matched simultaneously, the transformation impaired performance for all of the images; but when images were individually matched, the transformation improved perception of other race faces and discrimination of own race faces declined. Transformation of Japanese faces to show own race dimensions produced the same pattern of effects but failed to reach significance. The results provide support for both perceptual expertise and featural processing theories of own race bias. Results are interpreted with reference to face perception theories; implications for application and future study are discussed.