Performance of forensic facial comparison by morphological analysis across optimal and suboptimal CCTV settings |
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Affiliation: | Human Variation and Identification Research Unit, School of Anatomical Sciences, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, 7 York Road, Parktown 2193, South Africa |
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Abstract: | Facial comparison is an important yet understudied discipline in forensics. The recommended method for facial comparison in a forensic setting involves morphological analysis (MA) with the use of a facial feature list. The performance of this approach has not been tested across various closed-circuit television (CCTV) conditions. This is of particular concern as video and image data available to law enforcement is often varied and of subpar conditions. The present study aimed at testing MA across two types of CCTV data, representing ideal and less than ideal settings, also assessing which particular shortcomings arose from less-than-ideal settings. The study was conducted on a subset of the Wits Face Database arranged in a total of 225 face pools. Each face pool consisted of a target image obtained from either a high-definition digital CCTV camera or a low-definition analogue CCTV camera in monochrome, contrasted to 10 possible matches. The face pools were analysed and scored using MA and confusion matrices were used to analyse the outcomes. A notably high chance corrected accuracy (CCA) (97.3%) and reliability (0.969) was identified across the digital CCTV sample, while in the analogue CCTV sample MA appeared to underperform both in accuracy (CCA: 33.1%) and reliability (0.529). The majority of the errors in scoring resulted in false negatives in the analogue sample (75.2%), while across both CCTV conditions false positives were low (digital: 0.3%; analogue: 1.2%). Even though hit rates appeared deceptively high in the analogue sample, the various measures of performance used and particularly the chance corrected accuracy highlighted its shortfalls. Overall, CCTV recording quality appears closely associated to MA performance, despite the favourable error rates when using the Facial Identification Scientific Working Group feature list. |
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Keywords: | Forensic facial comparison Morphological analysis CCTV Analogue Digital Facial identification |
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