Forensic Facial Comparison: Current Status, Limitations, and Future Directions

Simple Summary Facial identification is an emerging field in forensic anthropology, largely due to the rise in closed circuit television presence worldwide, yet there is little published research in it. Our research group has conducted a series of studies testing the validity and reliability of the facial identification practice of morphological analysis. In this paper, we summarize the results of our studies and other latest advances in facial identification practice. In addition, we present a review of relevant technical literature on the limiting factors imposed on facial identification by closed circuit television, while making recommendations for practice and the future of this research niche based on a combination of our results and the technical know-how available. Facial identification research is a multidisciplinary task, with involvement from the field of anatomy, forensic anthropology, photography, image science, and psychology, among others. The value of this brief review is the bridging of these multiple disciplines to discuss the relevant needs and requirements of facial identification in forensic practice and future research. Global escalation of crime has necessitated the use of digital imagery to aid the identification of perpetrators. Forensic facial comparison (FFC) is increasingly employed, often relying on poor-quality images. In the absence of standardized criteria, especially in terms of video recordings, verification of the methodology is needed. This paper addresses aspects of FFC, discussing relevant terminology, investigating the validity and reliability of the FISWG morphological feature list using a new South African database, and advising on standards for CCTV equipment. Suboptimal conditions, including poor resolution, unfavorable angle of incidence, color, and lighting, affected the accuracy of FFC. Morphological analysis of photographs, standard CCTV, and eye-level CCTV showed improved performance in a strict iteration analysis, but not when using analogue CCTV images. Therefore, both strict and lenient iterations should be conducted, but FFC must be abandoned when a strict iteration performs worse than a lenient one. This threshold ought to be applied to the specific CCTV equipment to determine its utility. Chance-corrected accuracy was the most representative measure of accuracy, as opposed to the commonly used hit rate. While the use of automated systems is increasing, trained human observer-based morphological analysis, using the FISWG feature list and an Analysis, Comparison, Evaluation, and Verification (ACE-V) approach, should be the primary method of facial comparison.