The research aimed to explore the potential occurrence of the serial position effect and the own-race bias in facial recognition, and to explore whether these two socio-cognitive psychological phenomena had any influence on each other. Specifically, the researcher suggested that other-race facial recognition will show diminished U-type serial position curves in comparison to own-race facial recognition U-type serial position curves. This was done through a quasi-experimental design, testing 48 participants from an environmental consulting and ground engineering firm in Midrand, Johannesburg. Twelve (12) sets of slides showing either 5 black or 5 white faces were presented to participants, the sequence of faces was randomised and then displayed again to participants. Participants had to identify the original position in which the face was displayed (forcing a serial reconstruction task). Results yielded a U-type serial position curves for overall recognition, with a statistically significant effect for own-race bias effect. Specific interactions indicated that recognition for own-race facial stimuli exhibit clear serial position effect trends, whilst recognition of other-race facial stimuli recognition show increased recognition for the first, middle and last faces in a set. The researcher suggests that the results within this study could be attributed to the effect of an attentional primacy gradient within the Serial Information Processing model. However, further studies are required to eliminate numerous other confounding factors which may have played a role in the study. The results of this research have implications for the judicial system, in which false eyewitness identifications have profound consequences. / Dissertation (MA)--University of Pretoria, 2010. / Psychology / unrestricted

The Muslim headscarf conceals the hair and other external features of a face. For this reason it may have implications for the recognition of such faces. The experiments reported in this thesis aimed to investigate anecdotal reports, which suggested that headscarf wearing females are more difficult to recognise. This was done by employing a series of experiments which involved a yes/no recognition task. The stimuli that were used were images of South Asian females who were photographed wearing a Muslim headscarf (HS), with their own hair visible (H), and a third set of stimuli were produced in which their external features were cropped (CR). Most importantly, participants either took part in the condition in which the state of the external features remained the same between the learning and test stage (Same) or the condition in which they were switched between the two stages (Switch). In one experiment participants completed a Social Contact Questionnaire. Surprisingly, in the Same condition, there was no difference in the recognition rates of faces that were presented with hair, with headscarf, or cropped faces. However, participants in the Switch condition performed significantly worse than those in the Same condition. It was also found that there was no difference in the % of fixations to the external features between the Same and Switch condition, which implied that the drop in performance between the two conditions was not mediated by eye-movements. These results suggest that the internal and external features of a face are processed interactively and, although the external features were not fixated on, a manipulation to them caused a drop in performance. This was confirmed in a separate experiment in which participants were unable to ignore the external features when they were asked to judge the similarity of the internal features of pairs of faces. Pairs of headscarf faces were rated as being more similar compared to pairs of faces with hair. Finally, for one group of participants it was found that contact with headscarf-wearing females was positively correlated with the recognition of headscarf-wearing faces. It was concluded that the headscarf per se did not impair face recognition and that there is enough information in the internal features of a face for optimal recognition, however, performance was disrupted when the presence or absence of the headscarf was manipulated.

The Muslim headscarf conceals the hair and other external features of a face. For this reason it may have implications for the recognition of such faces. The experiments reported in this thesis aimed to investigate anecdotal reports, which suggested that headscarf wearing females are more difficult to recognise. This was done by employing a series of experiments which involved a yes/no recognition task. The stimuli that were used were images of South Asian females who were photographed wearing a Muslim headscarf (HS), with their own hair visible (H), and a third set of stimuli were produced in which their external features were cropped (CR). Most importantly, participants either took part in the condition in which the state of the external features remained the same between the learning and test stage (Same) or the condition in which they were switched between the two stages (Switch). In one experiment participants completed a Social Contact Questionnaire. Surprisingly, in the Same condition, there was no difference in the recognition rates of faces that were presented with hair, with headscarf, or cropped faces. However, participants in the Switch condition performed significantly worse than those in the Same condition. It was also found that there was no difference in the % of fixations to the external features between the Same and Switch condition, which implied that the drop in performance between the two conditions was not mediated by eye-movements. These results suggest that the internal and external features of a face are processed interactively and, although the external features were not fixated on, a manipulation to them caused a drop in performance. This was confirmed in a separate experiment in which participants were unable to ignore the external features when they were asked to judge the similarity of the internal features of pairs of faces. Pairs of headscarf faces were rated as being more similar compared to pairs of faces with hair. Finally, for one group of participants it was found that contact with headscarf-wearing females was positively correlated with the recognition of headscarf-wearing faces. It was concluded that the headscarf per se did not impair face recognition and that there is enough information in the internal features of a face for optimal recognition, however, performance was disrupted when the presence or absence of the headscarf was manipulated.

Abstract (Svenska) Den här undersökningen försöker ta reda på om orsaken till att människor bättre minns ansikten av sin egen etnicitet än ansikten med annan etnisk bakgrund ligger i mer holistisk än analytisk inkodning. Det testades även om kända och okända ansikten inkodas holistiskt eller analytiskt. Sammanlagt 51 personer deltog i undersökningen. Hälften av stimulusmaterialet var ljushyade (amerikaner av europeiskt ursprung) och hälften var mörkhyade (amerikaner av afrikanskt ursprung). 1/3 av stimulusmaterialet var bilder av mörka och ljusa kända personer. Uppgiften var att försöka känna igen bilderna då de visades på nytt med en förvrängning som skulle gynna antingen holistisk eller analytisk bearbetning. Resultaten visade att kända ansikten inkodades bättre än okända, och att skillnaden var större för holistisk än analytisk bearbetning. Skillnaden mellan ljusa och mörka ansikten gick i samma riktning, men var inte signifikant. / Abstract (English) The purpose of this study was to examine if the reason for Own Race Bias (ORB) – The fact that humans remember faces of their own ethnicity better than faces with another ethnic background/history – lies in the encoding mechanism. It also examined if celebrity faces were more holistically, and non-celebrity faces more analytically, encoded. Half of the stimulus material consisted of Caucasian Americans, and the other half of African Americans. One third of the faces belonged to celebrities. The task for the 51 participants was to recognize the faces. The results showed that celebrity faces were more often recognized than non-celebrity faces, and the difference was greater in holistic processing than in analytic. The difference between Caucasian and African faces showed the same tendency, but was not significant.

There has been a significant increase in the interest for the task of classifying demographic profiles i.e. race and ethnicity. Ethnicity is a significant human characteristic and applying facial image data for the discrimination of ethnicity is integral to face-related biometric systems. Given the diversity in the application of ethnicity-specific information such as face recognition and iris recognition, and the availability of image datasets for more commonly available human populations, i.e. Caucasian, African-American, Asians, and South-Asian Indians. A gap has been identified for the development of a system which analyses the full-face and its individual feature-components (eyes, nose and mouth), for the Pakistani ethnic group. An efficient system is proposed for the verification of the Pakistani ethnicity, which incorporates a two-tier (computer vs human) approach. Firstly, hand-crafted features were used to ascertain the descriptive nature of a frontal-image and facial profile, for the Pakistani ethnicity. A total of 26 facial landmarks were selected (16 frontal and 10 for the profile) and by incorporating 2 models for redundant information removal, and a linear classifier for the binary task. The experimental results concluded that the facial profile image of a Pakistani face is distinct amongst other ethnicities. However, the methodology consisted of limitations for example, low performance accuracy, the laborious nature of manual data i.e. facial landmark, annotation, and the small facial image dataset. To make the system more accurate and robust, Deep Learning models are employed for ethnicity classification. Various state-of-the-art Deep models are trained on a range of facial image conditions, i.e. full face and partial-face images, plus standalone feature components such as the nose and mouth. Since ethnicity is pertinent to the research, a novel facial image database entitled Pakistani Face Database (PFDB), was created using a criterion-specific selection process, to ensure assurance in each of the assigned class-memberships, i.e. Pakistani and Non-Pakistani. Comparative analysis between 6 Deep Learning models was carried out on augmented image datasets, and the analysis demonstrates that Deep Learning yields better performance accuracy compared to low-level features. The human phase of the ethnicity classification framework tested the discrimination ability of novice Pakistani and Non-Pakistani participants, using a computerised ethnicity task. The results suggest that humans are better at discriminating between Pakistani and Non-Pakistani full face images, relative to individual face-feature components (eyes, nose, mouth), struggling the most with the nose, when making judgements of ethnicity. To understand the effects of display conditions on ethnicity discrimination accuracy, two conditions were tested; (i) Two-Alternative Forced Choice (2-AFC) and (ii) Single image procedure. The results concluded that participants perform significantly better in trials where the target (Pakistani) image is shown alongside a distractor (Non-Pakistani) image. To conclude the proposed framework, directions for future study are suggested to advance the current understanding of image based ethnicity verification. / Acumé Forensic