## 3 Forensic Human Identification through the Analysis of Biomedical Images
### AI-Based Approaches for Facial Reconstruction  
Forensic facial reconstruction (or forensic facial approximation) is the process of recreating the face of an individual (whose identity is often not known) from his/her skeletal remains (Figure 8). Several works on the automation of facial reconstruction have been proposed during the last 15 years, giving rise to completely computerized and largely automated methods, often using CT scans as training sets [50; 51; 194; 195; 196; 197; 198]. [PERSON] et al. [194] presented a fully automatic procedure for craniofacial reconstruction, using a reference database of head CT scans. All reference images are automatically segmented into head volumes (enclosed by the external skin surface) and bone/skull volumes, both represented by a signed distance transform (sDT) map. The reference skull sDTs are non-linearly warped to the target skull sDT and this warping is applied to all reference skin sDTs. A linear combination of the warped reference skin sDTs is proposed as the reconstruction of the external skin surface of the target subject. Results on a pilot reference database (N = 20) show the feasibility of this approach, although further investigations are required. First, metal streak artefacts need to be removed from the images, since they possibly distort the reconstructions to an unacceptable extent. Second, the warping procedure needs to be examined more carefully, paying attention, on one hand, to better fitting the reference to the target skull and, on the other hand, to provide a smooth extrapolation of the warping. Third, other linear combinations besides the mere average need to be explored. Finally, a more extensive quantitative validation framework for the reconstructions needs to be carried out. [PERSON] et al. [196] proposed the automation of the reconstruction process through a data-driven 3D generative model of the face that was constructed using a database of CT head scans for a given skull. The reconstruction can be constrained based on prior knowledge such as age and/or weight. To determine whether or not these reconstructions have merit, geometric methods for comparing reconstructions against a gallery of facial images are proposed. First, Active Shape Models, a specific type of deformable model [199], are used to automatically detect a set of facial landmarks on each image. These landmarks are associated with 3D points on the reconstruction. Direct comparison of the reconstruction is problematic since, in general, the camera geometry used for image capture is unknown and there are uncertainties associated with the reconstruction and landmark detection processes. The first method of comparison uses constrained optimization to determine the optimal projection of the reconstruction onto the image. Residuals are, then, analyzed resulting in a ranking of the gallery. The second method uses boosting to learn which points are both reliable and discriminating. This results in a match/no-match classifier. [PERSON] et al. [48] described the common pipeline of modern facial approximation software. First, it is necessary that an expert examines the unknown skull in order to determine the BP. Then, a virtual replica of the skull is produced and represented according to the modeling parameters. A craniofacial template encoding face, skull and soft tissue information are derived from a head database. Then, an admissible geometric transformation drives the adaptation of the craniofacial template onto the unknown skull, according to the \"proximity\" between the skulls. As result, the template face is deformed onto the predicted face associated with the unknown skull, linking together information coming from both the database and the examination of the unknown skull. Finally, a skin texture and hairiness are added to the reconstructed face. [PERSON] et al. [50] developed a computerized method for estimating facial shape based on CT scans of 500 French individuals, Anthropological Facial Approximation in Three Dimensions.