Literature DB >> 33885153

Assessing the effect of facial disguises on forensic facial comparison by morphological analysis.

Nicholas Bacci1, Nanette Briers1, Maryna Steyn1.   

Abstract

Disguises are commonly used to mask a person's facial appearance in areas under closed-circuit television (CCTV) surveillance. While many studies attempted to understand the effects of disguises, such as hats and glasses, on facial recognition, limited studies have looked at disguises in forensic facial comparison. The aim of this study was to compare the outcomes of forensic facial comparison by morphological analysis (MA) in a CCTV sample with sunglasses and brimmed caps. The sample was obtained from the Wits Face Database and organized into 81 face pools of one target facial image wearing a disguise (cap or sunglasses) and 10 potential matching images. MA was conducted across face pools, and confusion matrices were used to assess the outcomes. Surprisingly, sunglasses had limited effect on MA performance both in accuracy (90.4%) and in reliability (κ = 0.798), while caps markedly decreased both accuracy (68.1%) and reliability (κ = 0.639). Error rates were associated primarily with false negatives in both samples (caps: 42.4%; sunglasses: 16.1%) despite the sample distribution favoring false-positive errors, which were very low (caps: 0.6%; sunglasses: 0%). Similarly to other studies, hats and caps were more harmful to correct identification when compared to sunglasses, which actually resulted in better accuracy than regular CCTV recordings. The effect of brimmed caps on accuracy was attributed to the overall loss of facial information caused. On training analysts, it may be helpful to instruct purposefully avoiding overreliance on easily disguised facial features, as other regions of the face also contain substantial feature information.
© 2021 American Academy of Forensic Sciences.

Keywords:  CCTV; caps; disguise; facial identification; forensic facial comparison; glasses; morphological analysis

Mesh:

Year:  2021        PMID: 33885153     DOI: 10.1111/1556-4029.14722

Source DB:  PubMed          Journal:  J Forensic Sci        ISSN: 0022-1198            Impact factor:   1.832


  3 in total

1.  Objective study of the facial parameters of observations in patients with type 2 diabetes mellitus by machine learning.

Authors:  Baozhi Cheng; Jianli Ma; Xiaolong Chen; Lingyan Yuan
Journal:  Ann Transl Med       Date:  2022-09

2.  3D-3D facial registration method applied to personal identification: Does it work with limited portions of faces? An experiment in ideal conditions.

Authors:  Daniele Gibelli; Andrea Palamenghi; Pasquale Poppa; Chiarella Sforza; Cristina Cattaneo; Danilo De Angelis
Journal:  J Forensic Sci       Date:  2022-02-28       Impact factor: 1.717

Review 3.  Forensic Facial Comparison: Current Status, Limitations, and Future Directions.

Authors:  Nicholas Bacci; Joshua G Davimes; Maryna Steyn; Nanette Briers
Journal:  Biology (Basel)       Date:  2021-12-03
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.