Interpretation of ante-mortem stature estimates in South Africans

Development of the Wits Face Database: an African database of high-resolution facial photographs and multimodal closed-circuit television (CCTV) recordings

Forensic facial comparison is a commonly used, yet under-evaluated method employed in medicolegal contexts across the world. Testing the accuracy and reliability of facial comparisons requires large scale controlled and matching facial image databases. Databases that contain images of individuals on closed-circuit television (CCTV), with matching formal and informal photographs are needed for this type of research. Although many databases are available, the majority if not all are developed in order to improve facial recognition and face detection algorithms through machine learning, with very limited if any measure of standardisation. This paper aims to review the available databases and describe the development of a high resolution, standardised facial photograph and CCTV recording database of male Africans. The database is composed of a total of 6220 standardised and uncontrolled suboptimal facial photographs of 622 matching individuals in five different views, as well as corresponding CCTV footage of 334 individuals recorded under different realistic conditions. A detailed description of the composition and acquisition process of the database as well as its subdivisions and possible uses are provided. The challenges and limitations of developing this database are also highlighted, particularly with regard to obtaining CCTV video recordings and ethics for a database of faces. The application process to access the database is also briefly described.

Validation of forensic facial comparison by morphological analysis in photographic and CCTV samples

Between the ever-increasing availability of surveillance evidence and expert-based forensic facial comparison being considered admissible in court, confirming its validity is paramount. Facial comparison is most commonly conducted using morphological analysis (MA), a largely untested feature-based approach. This study aimed at validating the current recommended practice of MA in both standardised and suboptimal surveillance samples. Face pools of 175 South African males were compiled with a series of facial photographs, using images from the Wits Face Database. The first 75 face pools consisted of wildtype (unstandardised) high-quality target photographs, while the remaining 100 face pools consisted of suboptimal closed-circuit television (CCTV) target images. Target images were compared to high-quality standardised photographs. Face pools were analysed using the Facial Identification Scientific Working Group's guidelines and feature list. Confusion matrices were used to determine the performance of MA in each cohort. MA was found highly accurate (chance-corrected accuracy (CCA): 99.1%) and reliable (κ = 0.921) in the photographic sample and less accurate (CCA: 82.6%) and reliable (κ = 0.743), in the CCTV sample. Higher false-positive and false-negative rates were noted for the CCTV sample, with the majority of errors resulting in false-negative outcomes. The decreased performance in the CCTV sample was attributed to various factors including image quality, angle of recording and lighting. Other studies testing facial comparison identified lower accuracies and reliability across various conditions. Better performance was found here and in other studies that included some form of facial feature list, reinforcing the importance of using a systematic facial feature list.

Updated lower limb stature estimation equations for a South African population group

One of the main steps in the identification of an unknown person, from their skeletal remains, is the estimation of stature. Measurements of intact long bones of the upper and lower extremities are widely used for this purpose because of the high correlation that exists between these bones and stature. In 1987, Lundy and Feldesman presented regression equations for stature estimation for the black South African population group based on measurements of bones from the Raymond A. Dart Collection of Human Skeletons. Local anthropologists have questioned the validity of these equations. Living stature measurement and magnetic resonance imaging scanograms of 58 adult volunteers (28 males and 30 females) representing the modern black South African population group were obtained. Physiological length of the femur (FEPL) and physiological length of the tibia (TPL) were measured on each scanogram and substituted into appropriate equations of Lundy and Feldesman (S Afr J Sci. 1987;83:54–55) to obtain total skeletal height (TSHL&F). Measured total skeletal height (TSHMeas) for each subject from scanograms was compared with TSHL&F. Both FEPL and TPL presented with significantly high positive correlations with TSHMeas. A comparison between TSHL&F and TSHMeas using a paired t-test, showed a statistically significant difference – an indication of non-validity of Lundy and Feldesman’s equations. New regression equations for estimation of living stature were formulated separately for male and female subjects. The standard error of estimate was low, which compared well with those reported for other studies that used long limb bones. Significance: • Statistically significant differences were observed between measured and estimated skeletal height, thus confirming non-validity of Lundy and Fieldsman’s (1987) equations for lower limb bones. • New regression equations for living stature estimation were formulated for femur and tibia lengths, and the low standard error of estimates of equations compared well to results from other studies.

Morphometric analysis of the humerus in an adult South African cadaveric sample

Recent studies using geometric morphometrics have shown that estimations of demographic parameters can be made using skeletal elements previously not thought useful for such purposes. This study used geometric morphometrics to assess humeral morphological variation in an adult South African sample, and evaluated the accuracy of sex and ancestry estimations based on this variation. Humeri of 1046 adult South African individuals (464 females, 582 males) were digitized. Data sets were rotated and scaled to a common centroid using Generalized Procrustes Analysis. Mean centroid sizes between groups were compared using parametric tests, while morphological variation was evaluated using multivariate analyses. Discriminant Function Analysis coupled with leave-one-out cross-validation tests were used to assess the reliability of sex and ancestry classifications based on this variation. Male humeri were relatively larger and presented with morphological features indicative of larger muscle mass and smaller carrying angles than females. White individuals had relatively larger but morphologically less robust humeri than Black or Coloured individuals, likely a reflection of both genetic and socio-economic differences between the groups as enforced under Apartheid law. When sex and ancestry were assessed together, similar variations were detected than when either parameter was individually assessed. Classification accuracy was relatively low when sex was independently assessed (73.3%), but increased when considered in conjunction with ancestry, indicating greater variation between-groups (ancestry) than within-groups. Ancestry estimation accuracies exceeded 80%, even for the highly diverse Coloured group. Classification accuracies of sex-ancestry groups all exceeded 76%. These results show that humerus morphological variation is present and may be used to estimate parameters, such as sex and ancestry, even in complex groups such as the Coloured sample of this study.

The accuracy of the anatomical method for stature estimation in Black South African females

The anatomical method is considered the most accurate stature estimation method, but investigation has shown that it continuously underestimates stature. This underestimation is believed to be related to the use of universal soft tissue correction factors. Therefore, the aim of this study was to assess the accuracy of the soft tissue correction factors in a living population of Black South African females and to subsequently calculate a new soft tissue correction factor, specific for stature estimation in this population group. Thirty Black South African adult females voluntarily participated in this study and underwent a full body Magnetic Resonance Imaging (MRI) scan. Living stature was measured with a stadiometer and total skeletal height (TSH) was calculated from the MRI measurements. Stature was estimated from the TSH of each participant using Fully's (1956) [17], Raxter et al.'s (2006) [38] and Bidmos and Manger's (2012) [5] methods. Results indicated strong, statistically significant positive correlations between living and estimated statures, however, paired t-tests revealed that living stature was significantly underestimated using Fully's and Raxter et al.'s methods, while the method by Bidmos and Manger significantly overestimated stature. A lack of statistically significant correlations between soft tissue correction factors and the total skeletal height was found. Likewise, an absence of statistically significant correlations between age and the estimation error, with and without age adjustments were also observed. A new soft tissue correction factor, specific for stature estimation in Black South African females was calculated. The newly proposed regression equation presented improved stature estimation accuracies for this population group.

An alternative approach for estimating stature from long bones that is not population- or group-specific

An accurate and precise estimate of stature can be very useful in the analysis of human remains in forensic cases. A problem with many stature estimation methods is that an unknown individual must first be assigned to a specific group before a method can be applied. Group membership has been defined by sex, age, year of birth, race, ancestry, continental origin, nationality or a combination of these criteria. Univariate and multivariate sex-specific and generic equations are presented here that do not require an unknown individual to be assigned to a group before stature is estimated. The equations were developed using linear regression with a sample (n=244) from the Terry Collection and tested using independent samples from the Forensic Anthropology Databank (n=136) and the Lisbon Collection (n=85). Tests with these independent samples show that (1) the femur provides the best univariate results; (2) the best multivariate equation includes the humerus, femur and tibia lengths; (3) a generic equation that does not require an unknown to first be assigned to a given category provides the best results most often; (4) a population-specific equation does not provide better results for estimating stature; (5) sex-specific equations can provide slightly better results in some cases; however, estimating the wrong sex can have a negative impact on precision and accuracy. With these equations, stature can be estimated independently of age at death, sex or group membership.

Population differences in the postcrania of modern South Africans and the implications for ancestry estimation

The cranium is widely recognized as the most important skeletal element to use when evaluating population differences and estimating ancestry. However, the cranium is not always intact or available for analysis, which emphasizes the need for postcranial alternatives. The purpose of this study was to quantify postcraniometric differences among South Africans that can be used to estimate ancestry. Thirty-nine standard measurements from 11 postcranial bones were collected from 360 modern black, white and coloured South Africans; the sex and ancestry distribution were equal. Group differences were explored with analysis of variance (ANOVA) and Tukey's honestly significant difference (HSD) test. Linear and flexible discriminant analysis (LDA and FDA, respectively) were conducted with bone models as well as numerous multivariate subsets to identify the model and method that yielded the highest correct classifications. Leave-one-out (LDA) and k-fold (k=10; FDA) cross-validation with equal priors were used for all models. ANOVA and Tukey's HSD results reveal statistically significant differences between at least two of the three groups for the majority of the variables, with varying degrees of group overlap. Bone models, which consisted of all measurements per bone, resulted in low accuracies that ranged from 46% to 63% (LDA) and 41% to 66% (FDA). In contrast, the multivariate subsets, which consisted of different variable combinations from all elements, achieved accuracies as high as 85% (LDA) and 87% (FDA). Thus, when using a multivariate approach, the postcranial skeleton can distinguish among three modern South African groups with high accuracy.

Estimation of stature from lengths of index and ring fingers in a North-eastern Indian population

Forensic anthropology involves identification of human remains in a legal situation. Along with the other three parameters of forensic anthropology, i.e., age, sex and ethnicity, stature estimation is an essential element of medico-legal investigations when identifications of unknown dismembered remains are involved. The present study was conducted with an aim to find the correlation between stature and the lengths of the index and ring fingers and to derive linear and multiple regression models for estimation of adult stature from the index finger and ring finger measurements. The subjects chosen for the study were composed of adult individuals belonging to the "Rajbanshi", an ethnic community of North-eastern India. A total of 500 adults (250 males and 250 females) aged between 18 years and 60 years took part in the study. All the measurements were taken using standard techniques. Stature, index finger length and ring finger length were significantly longer in the males than the females. The correlation coefficient (r) between stature and finger lengths was observed to be positive and statistically significant. Linear and multiple regression models were derived for estimation of stature from a length of index and ring fingers. The predictive accuracy of stature estimation was higher for the females than the males. It was observed that the values of the correlation coefficient (r) and the coefficient of determination (R(2)) increased in multiple regression models when compared to the linear regression models. The study also focuses on the usability of sex-specific regression models in forensic casework. The study concludes that such regression models, as those derived in the present work, can be of significant utility in the estimation of stature.