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The morphological assessment of facial features using photographs has played an important role in forensic anthropology. The analysis of anthropometric landmarks for determining facial dimensions and angles has been considered in diverse forensic areas. Hence, the quantification of the error associated to the location of facial landmarks seems to be necessary when photographs become a key element of the forensic procedure. In this work, we statistically evaluate the inter- and intra-observer dispersions related to the facial landmark identification on photographs. In the inter-observer experiment, a set of 18 facial landmarks was provided to 39 operators. They were requested to mark only those that they could precisely place on 10 photographs with different poses (frontal, oblique, and lateral views). The frequency of landmark location was studied together with their dispersion. Regarding the intra-observer evaluation, three participants identified 13 facial points on five photographs classified in the frontal and oblique views. Each landmark location was repeated five times at intervals of at least 24 h. The frequency results reveal that glabella, nasion, subnasale, labiale superius, and pogonion obtained the highest location frequency in the three image categories. On the contrary, the lowest rate corresponds to labiale inferius and menton. Meanwhile, zygia, gonia, and gnathion were significantly more difficult to locate than other facial landmarks. They produced a significant effect on the dispersion depending on the pose of the image where they were placed, regardless of the type of observer that positioned them. In particular, zygia and gonia presented a statistically greater variation in the three image poses, while the location of gnathion is less precise in oblique view photographs. Hence, our findings suggest that the latter landmarks tend to be highly variable when determining their exact position.

Craniofacial superimposition can provide evidence to support that some human skeletal remains belong or not to a missing person. It involves the process of overlaying a skull with a number of ante mortem images of an individual and the analysis of their morphological correspondence. Within the craniofacial superimposition process, the skull-face overlay stage just focuses on achieving the best possible overlay of the skull and a single ante mortem image of the suspect. Although craniofacial superimposition has been in use for over a century, skull-face overlay is still applied by means of a trial-and-error approach without an automatic method. Practitioners finish the process once they consider that a good enough overlay has been attained. Hence, skull-face overlay is a very challenging, subjective, error prone, and time consuming part of the whole process. Though the numerical assessment of the method quality has not been achieved yet, computer vision and soft computing arise as powerful tools to automate it, dramatically reducing the time taken by the expert and obtaining an unbiased overlay result. In this manuscript, we justify and analyze the use of these techniques to properly model the skull-face overlay problem. We also present the automatic technical procedure we have developed using these computational methods and show the four overlays obtained in two craniofacial superimposition cases. This automatic procedure can be thus considered as a tool to aid forensic anthropologists to develop the skull-face overlay, automating and avoiding subjectivity of the most tedious task within craniofacial superimposition., (Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.)