Facial recognition for disaster victim identification.

Mass disaster events can result in high levels of casualties that need to be identified. Whilst disaster victim identification (DVI) relies on primary identifiers of DNA, fingerprints, and dental, these require ante-mortem data that may not exist or be easily obtainable. Facial recognition technology may be able to assist. Automated facial recognition has advanced considerably and access to ante-mortem facial images are readily available. Facial recognition could therefore be used to expedite the DVI process by narrowing down leads before primary identifiers are made available. This research explores the feasibility of using automated facial recognition technology to support DVI. We evaluated the performance of a commercial-off-the-self facial recognition algorithm on post-mortem images (representing images taken after a mass disaster) against ante-mortem images (representing a database that may exist within agencies who hold face databases for identity documents (such as passports or driver's licenses). We explored facial recognition performance for different operational scenarios, with different levels of face image quality, and by cause of death. Our research is the largest facial recognition evaluation of post-mortem and ante-mortem images to date. We demonstrated that facial recognition technology would be valuable for DVI and that the performance varies by image quality and cause of death. We provide recommendations for future research.

The performance of practitioners conducting facial comparisons on images of children across age.

Determining the identity of children is critical to aid in the fight against child exploitation, as well as for passport control and visa issuance purposes. Facial image comparison is one method that may be used to determine identity. Due to the substantial amount of facial growth that occurs in childhood, it is critical to understand facial image comparison performance across both chronological age (the age of the child), and age variation (the age difference between images). In this study we examined the performance of 120 facial comparison practitioners from a government agency on a dataset of 23,760 image pairs selected from the agency's own database of controlled, operational images. Each chronological age in childhood (0-17 years) and age variations ranging from 0-10 years were examined. Practitioner performance was found to vary considerably across childhood, and depended on whether the pairs were mated (same child) or non-mated (different child). Overall, practitioners were more accurate and confident with image pairs containing older children, and also more accurate and confident with smaller age variations. Chronological age impacted on accuracy with mated pairs, but age variation did not. In contrast, both age and age variation impacted on accuracy with non-mated pairs. These differences in performance show that changes in the face throughout childhood have a significant impact on practitioner performance. We propose that improvements in accuracy may be achievable with a better understanding of which facial features are most appropriate to compare across childhood, and adjusting training and development programs accordingly.

How academics face the world: a study of 5829 homepage pictures.

It is now standard practice, at Universities around the world, for academics to place pictures of themselves on a personal profile page maintained as part of their University's web-site. Here we investigated what these pictures reveal about the way academics see themselves. Since there is an asymmetry in the degree to which emotional information is conveyed by the face, with the left side being more expressive than the right, we hypothesised that academics in the sciences would seek to pose as non-emotional rationalists and put their right cheek forward, while academics in the arts would express their emotionality and pose with the left cheek forward. We sourced 5829 pictures of academics from their University websites and found that, consistent with the hypotheses, there was a significant difference in the direction of face posing between science academics and English academics with English academics showing a more leftward orientation. Academics in the Fine Arts and Performing Arts however, did not show the expected left cheek forward bias. We also analysed profile pictures of psychology academics and found a greater bias toward presenting the left check compared to science academics which makes psychologists appear more like arts academics than scientists. These findings indicate that the personal website pictures of academics mirror the cultural perceptions of emotional expressiveness across disciplines.