Perceptual expertise in forensic facial image comparison

Abstract

Forensic facial identification examiners are required to match the identity of faces in images that vary substantially, owing to changes in viewing conditions and in a person's appearance. These identifications affect the course and outcome of criminal investigations and convictions. Despite calls for research on sources of human error in forensic examination, existing scientific knowledge of face matching accuracy is based, almost exclusively, on people without formal training. Here, we administered three challenging face matching tests to a group of forensic examiners with many years' experience of comparing face images for law enforcement and government agencies. Examiners outperformed untrained participants and computer algorithms, thereby providing the first evidence that these examiners are experts at this task. Notably, computationally fusing responses of multiple experts produced near-perfect performance. Results also revealed qualitative differences between expert and non-expert performance. First, examiners' superiority was greatest at longer exposure durations, suggestive of more entailed comparison in forensic examiners. Second, experts were less impaired by image inversion than nonexpert students, contrasting with face memory studies that show larger face inversion effects in high performers. We conclude that expertise in matching identity across unfamiliar face images is supported by processes that differ qualitatively from those supporting memory for individual faces.

A Framework for Harmonizing Forensic Science Practices and Digital/Multimedia Evidence

“…Facial identification methods have been validated through empirical studies and found to be accurate (White et al, 2015).…”

Metrological characterization of 3D biometric face recognition systems in actual operating conditions

“…Cam1-2, Cam3-4, Cam5-6) is reported. In particular, at first, the comparison of all uncertainty components involved in (4) and (5) is made. Then, the recognition performance of the systems is presented by comparing suitable figures of merit, typically adopted for the analysis of classification systems [40].…”

“…Moreover, FR systems exploit digital images and photogrammetry to provide contact-less identification [2], [3]. Those systems spread widely due to an increasing demand in the fields of security assurance and automatic identity verification [4] - [6]. In fact, it is possible to find applications showing good performances and good maturity [7] when operating under constrained conditions, so that the person to be identified lies in a controlled environment and faces the camera(s) with a specified orientation.…”

The emergence of expertise with novel objects

“…Fingerprint examiners are also more accurate than novices at discriminating briefly presented prints, although their performance improves even more when given more time (Thompson & Tangen, 2014). Facial recognition experts show a similar advantage when matching briefly presented unfamiliar faces (White et al, 2015).…”

“…prints Thompson, Tangen & McCarthy, 2013), and particular groups of facial recognition examiners, whose task it is to compare unfamiliar faces for identity, also display superior performance compared to novices (White, Phillips, Hahn, Hill & O'Toole, 2015; although see White, Kemp, Jenkins, Matheson & Burton, 2014). These examiners face a formidable recognition task day to day.…”