## 1 Introduction  
Forensic Face Recognition (FFR) has become a critical tool in investigations due to the proliferation of surveillance cameras or mobile phones that continuously produce trace images. It consists of comparing images representing faces and evaluating the results in a forensic contest. The comparison involves two images, the trace image, which is typically taken under uncontrolled conditions, and the reference image, which is taken under controlled conditions. In the trace image, the identity of the depicted subject is contested or uncertain. In the reference image the identity of the subject is known; this one is the mug shot. A traditional mug shot is a front and side view of a person from the shoulder up, taken by law enforcement agencies. Its primary purpose is to provide a photographic record of arrested individuals for identification by victims, the public, and investigators. In a mug shot, the facial expression must remain neutral, the eyes must be open, and no hair or other objects should obscure the face, as required by police standards for passport photographs. In forensics images are used for different purposes. The ultimate aim of FFR is the evaluative purpose, that is to interpret the result of the comparison between the trace and mug shot of the suspect to present it as evidence in court [1]. As the FFR represents a mean to determine the strength of evidence used in a court of law, it must meet different legal requirement depending on the country. The specific guidelines regarding procedures, quality principles, and approaches, are those provided by the European Network of Forensic Science Institute (ENFSI) and by the Facial Identification Scientific Working Group (FISWG) to guarantee the reliability of the analysis process. Both ENFSI [2] and FISWG [3] define all the workflow of FFR and also which method may be used for image comparison. Among them, the most recommended is the morphological analysis, whereby facial images are compared feature by feature methodically using a check list. Currently, 2D mug shots are used in FFR, but the increasing number of surveillance (CCTV) cameras is creating a large repository of trace images that need to be matched against millions of existing mug shots. The comparison with traditional front and side mug shots is complicated by the fact that CCTV cameras mainly capture images from above. This is one of the problems that the investigator encounters: the images of the anonymous person are captured by cameras with significantly different angles than those of the conventional mug shot (front and right profile). For this reason, facial comparison may not be possible (ENFSI) or may even produce false negatives. Figure 1[2] shows the variation in the appearance of the same individual at different camera angles. New research in the field of the forensic science is exploring the benefits of new technologies and the use of 3D tools in the analysis, interpretation, and presentation of forensic data is increasing in the criminal justice system [4]. As a result, the evolving needs of the forensic community are moving away from traditional portrait-based facial recognition methods [5] toward a 3D mug shot. Unlike 2D mug shots, which are fixed in perspective, 3D mug shots are flexible in perspective, improving comparison according to the investigators' needs. Nevertheless, the creation of a 3D mug shot is a more challenging process than that of a 2D one. This is due to the necessity for highly precise 3D reconstruction to prevent the distortion of the subject's facial features. The FISWG have developed a detailed facial features checklist document to produce standardization in examinations. Every facial component is described by means of characteristics and descriptors such as size and shape. Moreover, it specifies that, with the term distance, the precise value of a dimension is not the intended determinant, but rather the relative size of this dimension with reference to a morphological analysis.