Facial morphometric differences across face databases: influence of ethnicities and sex

The scientific need for standardized, high-quality facial stimuli has driven the creation of several face image databases in recent years. These stimuli are particularly important in facial asymmetry research. However, previous studies have reported facial anthropometric differences across a variety of ethnicities. This highlights the need to investigate whether these differences can also impact the use of face image databases, particularly in facial asymmetry research. In this study, we investigated facial asymmetry-based morphometric differences between the multi-ethnic Chicago Face Database (CFD) and the LACOP Face Database, which is composed of Brazilian subjects. We found reliable differences in facial asymmetry between the two databases, which were related to ethnic groups. Specifically, differences in eye and mouth asymmetry seem to drive these differences. The asymmetry-based morphometric differences among databases and ethnicities found in this study reinforce the necessity of creating multi-ethnic face databases

Exploring skeletal asymmetry and indicators of developmental stress in a South African sample

Dissertation (MSc (Anatomy))--University of Pretoria, 2022.Biological anthropologists have shown great interest in understanding health and disease and its correlation to skeletal asymmetry. Fluctuating asymmetry, which is defined as the random deviation from perfect symmetry resulting in inequality in size or shape of bilateral traits, is often used to understand this correlation. Literature has shown that fluctuating asymmetry results from developmental instabilities and could be indicative of developmental stressors and an individual’s quality of life. Skeletal asymmetry and its correlation to different developmental stressors provide invaluable information regarding the interpretation of skeletal variation often observed among individuals. The understanding of human skeletal variation has many applications, ranging from forensic skeletal identification to facial surgery. While traditional methods for studying facial and dental asymmetry have been used in the past, the methods can be methodologically challenging, and not always practical in clinical settings. As such, virtual biological anthropology has become an increasingly popular alternative. Among the imaging modalities, micro-focus X-ray computed tomography (micro-XCT) is often considered as the gold standard, because of its non-invasive and non-destructive properties, as well as its remarkably high resolution and its consistency compared to other micro-XCT systems. Micro-XCT imaging has thus proven to be extremely useful for better evaluation of facial structures, with detailed images that can assist in identifying and quantifying facial asymmetry, especially when employed in conjunction with geometric morphometrics. Therefore, this study aimed to assess facial asymmetry in a South African population using micro-XCT and further explore the link between asymmetry and developmental stress. One hundred and fifteen individuals (59 black South Africans and 56 white South Africans, with 57 females and 58 males) and their associated micro-XCT scans, sourced from the Pretoria Bone Collection (University of Pretoria) were analysed to evaluate facial asymmetry. Anatomical landmarks were employed to take a series of cranial measurements and collect 3D coordinate data for geometric morphometric analysis. The measurements and extraction of 3D coordinate data were performed on 3D models virtually extracted from micro-XCT scans of crania of the same individual. Once collected, fluctuating asymmetry indices were calculated. The entire skeleton of the individuals was assessed for pathological lesions linked to nutritional disease and to assess the overall link to developmental stress of the individuals. The location and number of lesions was recorded for each individual. Statistical analyses were employed to assess intra- and inter-observer reliability for landmarks, measurements, and pathology analysis; to examine any significant differences between the left and right distances and shapes for measurements and geometric morphometric analysis, respectively; and finally, to evaluate the correlation between the presence of pathological lesions and the degree of asymmetry expressed in an individual. This study showed that the orbits, nasion and temporal regions expressed a high magnitude of asymmetry, particularly in black South African females. However, no link was found between asymmetry and signs of developmental stress. Thus, more research can be done to understand how, and when developmental stressors may influence skeletal asymmetry.AnatomyMSc (Anatomy)Unrestricte

An Investigation into the Performance of Ethnicity Verification Between Humans and Machine Learning Algorithms

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 Forensi