Recognizability of computer-generated facial approximations in an automated facial recognition context for potential use in unidentified persons data repositories: Optimally and operationally modeled conditions.

Currently in the United States, the remains of thousands of unidentified human decedents are housed in medical, law enforcement, and forensic facilities throughout the country. A number of digital data repositories have been established to curate and disseminate the details of these unidentified decedent cases; some repositories also maintain records of missing persons. Although a cross-reference for textual data similarity occurs between the missing persons and unidentified decedent records in some repositories, no repository is currently known to employ an image analysis technology for cross-referencing image data. Results suggest that the computer-generated facial approximations used in this research were consistently included in prioritized candidate lists when used in an automated facial recognition context. Two concurrent studies exploring the specific use-case discussed here were executed. The first employed an optimally-conditioned facial image gallery (g=6159) (i.e., a gallery comprised of highly consistent facial images), a research design intended to establish the ceiling performance of the combined use of the two software programs employed. The second employed a gallery (g=1816) compiled from a real-world dataset of missing persons' facial images, a research design intended to inform potential operational performance when using the highly varied facial images typically comprising public databases. Multiple types of facial approximations (reconstructions) with varying degrees of weight adjustments, age adjustments, or the presence (or absence) of visible eyes, and combinations of these variables, were evaluated. Overall, in the larger, optimally modeled study, 53% of the facial approximations for the t=159 test subjects examined were matched to his or her corresponding life photo within the top 50 images of a candidate list generated from a blind (unrestricted) search of the highly consistent gallery (g=6159). In the operationally modeled study, 31% of the test subjects' (t=16) facial approximations were matched to their corresponding life photos within the top 50 images of a candidate list generated from a blind search of the gallery populated with images from an operational dataset (g=1816). As anticipated, candidate list inclusion rates improved with the use of demographic filters. No significantly different inclusion rates were observed between the sex or age cohorts examined. Significant differences were, however, observed across population cohorts. Entities curating missing and unidentified decedent records may benefit from a paired implementation of facial recognition technology and computer-generated approximations as part of a comprehensive investigative strategy for the specific envisioned use-case discussed in this research. Published by Elsevier B.V.