Towards a method for determining age ranges from faces of juveniles on photographs

Forensic Anthropology and Archaeology in Denmark

In this paper, we provide a brief overview of the status of forensic anthropology and forensic archeology in Denmark, as well as related information about education, research, and skeletal collections. Forensic anthropologists mainly deal with the examination of unidentified skeletal remains. Some special tasks include cranial trauma analysis of the recently deceased, advanced 3D visualization from CT scanning of homicide cases, and stature estimation of perpetrators using surveillance videos. Forensic anthropologists are employed at one of Denmark’s three departments of forensic medicine (in Copenhagen, Odense, and Aarhus) and have access to advanced imaging equipment (e.g., CT and MR scanning, surface scanners, and 3D printers) for use in both their requisitioned work and their research. Extensive research is conducted on different topics, such as the health and diseases of past populations, age estimation, and human morphology. Research is based on skeletal material from the archeological collections housed in Copenhagen and Odense or on CT data from the recently deceased. There is no full degree in forensic anthropology in Denmark, but elective courses and lectures are offered to students at different levels and to people from different professional backgrounds.

Forensic archaeology is a relatively new field of expertise in Denmark, and relevant cases are rare, with only one or two cases per year. No forensic archeologists are officially employed in any of the departments of forensic medicine. Until recently, the Special Crime Unit of the police handled crime scene investigations involving excavations, but with the option of enlisting the help of outside specialists, such as archaeologists, anthropologists, and pathologists. An official excavation work group was established in 2015 under the lead of the Special Crime Unit of the police with the aim of refining the methods and procedures used in relevant criminal investigations. The group is represented by five police officers from the Special Crime Scene Unit, a police officer from the National Police Dog Training center, the two archaeologists from Moesgaard Museum, a forensic anthropologist from the Department of Forensic Medicine (University of Copenhagen), and a forensic pathologist from the Department of Forensic Medicine (University of Aarhus).

Age verification using random forests on facial 3D landmarks

Three-dimensional facial images are becoming more and more widespread. As such images provide more information about facial morphology than 2D imagery, they show great promise for use in future forensic applications, including age estimation and verification. This paper proposes an approach using random forests, a machine learning method, to develop and test models for classification of legal age thresholds (15 years and 18 years) using 3D facial landmarks. Our approach was developed on a set of 3D facial scans from 394 Czech individuals (194 males and 200 females) aged between 10 and 25 years. The dataset was retrieved from a sizable database of Central European faces - The FIDENTIS 3D Face Database. Three main types of input variables were processed using random forests: I) shape (size-invariant) coordinates of 3D landmarks, II) size and shape coordinates of 3D landmarks, and III) inter-landmark distances, angles and indices. The performance rates for the combinations of variables and age threshold were expressed in terms of sensitivity and specificity. The overall accuracy rates varied from 71.4%-91.5% (when the male and female samples were pooled). In general, higher accuracy was achieved for the age limit of 18 years than for 15 years. Whereas size-variant variables showed a better performance rate for the age limit of 15 years, the size-invariant variables (i.e., shape variables) were better for classifying individuals under 18 years. The verification models grounded on traditional variables (distances, angles, indices) yielded consistently higher performance rates on females than on males, whereas the inverse trend was observed for the models built on 3D coordinates. The results indicate that age verification based on 3D facial data with processing by the random forests method has high potential for further forensic or biometric applications.

Estimating sex and age from a face: a forensic approach using machine learning based on photo-anthropometric indexes of the Brazilian population

The facial analysis permits many investigations, some of the most important of which are craniofacial identification, facial recognition, and age and sex estimation. In forensics, photo-anthropometry describes the study of facial growth and allows the identification of patterns in facial skull development, for example, by using a group of cephalometric landmarks to estimate anthropological information. Previous works presented, as indirect applications, the use of photo-anthropometric measurements to estimate anthropological information such as age and sex. In several areas, automation of manual procedures has achieved advantages over and similar measurement confidence as a forensic expert. This manuscript presents an approach using photo-anthropometric indexes, generated from frontal faces cephalometric landmarks of the Brazilian population, to create an artificial neural network classifier that allows the estimation of anthropological information, in this specific case age and sex. This work is focused on four tasks: (i) sex estimation on ages from 5 to 22 years old, evaluating the interference of age on sex estimation; (ii) age estimation from photo-anthropometric indexes for four age intervals (1 year, 2 years, 4 years, and 5 years); (iii) age group estimation for thresholds of over 14 and over 18 years old; and; (iv) the provision of a new data set, available for academic purposes only, with a large and complete set of facial photo-anthropometric points marked and checked by forensic experts, measured from over 18,000 faces of individuals from Brazil over the last 4 years. The proposed binary classifier obtained significant results, using this new data set, for the sex estimation of individuals over 14 years old, achieving accuracy values higher than 0.85 by the F₁ measure. For age estimation, the accuracy results are 0.72 for the F₁ measure with an age interval of 5 years. For the age group estimation, the F₁ measures of accuracy are higher than 0.93 and 0.83 for thresholds of 14 and 18 years, respectively.

Facial Anthropometric Proportion of Chinese Han Nationality

Facial anthropometric measurements play an important part not only in forensic cases but also in clinical treatments. The utilization of 2D photograph methods in facial anthropometric studies to found database with age, gender, ethnicity, and region was expanded by other races but little for Han nationality. This study was undertaken to describe reference ranges of facial anthropometric proportions of Han nationality and compare the anthropometric characteristics with other ethnicities. Our subjects focused on full-face photos of Han nationality in South China which consisted of 1176 healthy person (425 adult males, 421 adult females and 157 underage boys and 173 underage girls). Eight anthropometric landmarks on photos were examined by ImageJ software, and 7 anthropometric ratios were analyzed. The results indicated sex- and age- and ethnics-related anthropometric variations in Chinese Han nationality in South China. For adults, females have larger ratios in intercanthal-nasal width and lip height index and smaller nose width index; for impubes, boys were larger in lip height index and smaller in lip width ratios than girls, but as age achieved, the underage boys and girls exhibited a significantly larger nose width index and lip width index, smaller canthal index, intercanthal-nasal width and lip height index. Comparing with Japanese, India, North American and Persian, Chinese Han showed great difference in facial anthropometric proportions.

Estimating a child's age from an image using whole body proportions

The use and distribution of child pornography is an increasing problem. Forensic anthropologists are often asked to estimate a child's age from a photograph. Previous studies have attempted to estimate the age of children from photographs using ratios of the face. Here, we propose to include body measurement ratios into age estimates. A total of 1603 boys and 1833 girls aged 5-16 years were measured over a 10-year period. They are 'Cape Coloured' children from South Africa. Their age was regressed on ratios derived from anthropometric measurements of the head as well as the body. Multiple regression equations including four ratios for each sex (head height to shoulder and hip width, knee width, leg length and trunk length) have a standard error of 1.6-1.7 years. The error is of the same order as variation of differences between biological and chronological ages of the children. Thus, the error cannot be minimised any further as it is a direct reflection of a naturally occurring phenomenon.

Quantitative assessment of the facial features of a Mexican population dataset

The present study describes the morphological variation of a large database of facial photographs. The database comprises frontal (386 female, 764 males) and lateral (312 females, 666 males) images of Mexican individuals aged 14-69 years that were obtained under controlled conditions. We used geometric morphometric methods and multivariate statistics to describe the phenotypic variation within the dataset as well as the variation regarding sex and age groups. In addition, we explored the correlation between facial traits in both views. We found a spectrum of variation that encompasses broad and narrow faces. In frontal view, the latter is associated to a longer nose, a thinner upper lip, a shorter lower face and to a longer upper face, than individuals with broader faces. In lateral view, antero-posteriorly shortened faces are associated to a longer profile and to a shortened helix, than individuals with longer faces. Sexual dimorphism is found in all age groups except for individuals above 39 years old in lateral view. Likewise, age-related changes are significant for both sexes, except for females above 29 years old in both views. Finally, we observed that the pattern of covariation between views differs in males and females mainly in the thickness of the upper lip and the angle of the facial profile and the auricle. The results of this study could contribute to the forensic practices as a complement for the construction of biological profiles, for example, to improve facial reconstruction procedures.

Modelling of facial growth in Czech children based on longitudinal data: Age progression from 12 to 15 years using 3D surface models

Dealing with the increasing number of long-term missing children and juveniles requires more precise and objective age progression techniques for the prediction of their current appearance. Our contribution includes detailed and real facial growth information used for modelling age progression during adolescence. This study was based on an evaluation of the overall 180 three-dimensional (3D) facial scans of Czech children (23 boys, 22 girls), which were longitudinally studied from 12 to 15 years of age and thus revealed the real growth-related changes. The boys underwent more marked changes compared with the girls, especially in the regions of the eyebrow ridges, nose and chin. Using modern geometric morphometric methods, together with their applications, we modelled the ageing and allometric trajectories for both sexes and simulated the age-progressed effects on facial scans. The facial parts that are important for facial recognition (eyes, nose, mouth and chin) all deviated less than 0.75mm, whereas the areas with the largest deviations were situated on the marginal parts of the face. The mean error between the predicted and real facial morphology obtained by modelling the children from 12 to 15 years of age was 1.92mm in girls and 1.86mm in boys. This study is beneficial for forensic artists as it reduces the subjectivity of age progression methods.