Assessing Recognition Potential in Forensic Facial Depictions: The Role of Texture, Display Conditions and Finishing Techniques

Greenway, E (2025) Assessing Recognition Potential in Forensic Facial Depictions: The Role of Texture, Display Conditions and Finishing Techniques. Doctoral thesis, Liverpool John Moores University.

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Abstract

Forensic facial depiction can facilitate the identification of unknown human remains by presenting an estimation of individual appearance, with the aim of eliciting recognition and providing investigative leads for authorities. These depictions are presented in various ways, shaped by artistic and technical decisions that influence recognisability. This study examines how specific choices regarding textural inclusion, display formats, and finishing techniques impact the effectiveness of forensic facial depictions, employing both a practice-based exploration and a complementary experimental analysis. The practice-based component involved the creation and digital manipulation of facial depictions from familiar individuals, designed to simulate forensic constraints and presentation contexts. These depictions were evaluated in a series of experimental tasks, where participants attempted to recognise individuals under systematically varied conditions of texture, display, and finishing effects. The analysis utilised Generalised Linear Mixed Modelling (GLMM) to assess the impact of these variables on correct identification rates, providing a robust framework to model recognition outcomes while accounting for random effects across participants and facial depictions. The key finding is that multiple viewpoints should be included in forensic practice. Other findings are that finishing effects and display conditions that soften, but do not exclude, external features significantly enhance recognition by focusing on internal facial details. Repeated presentation also consistently improves recognition but requires careful control to avoid false positives in practical settings. The findings underscore the potential of using GLMM in evaluating forensic methodologies and contribute a toolkit for enhancing recognisability, advancing both forensic practice and investigative outcomes.

Item Type:	Thesis (Doctoral)
Uncontrolled Keywords:	Forensic Facial Depiction; Forensic Imaging Optimisation; Face Recognition; Generalised Linear Mixed Modelling (GLMM)
Subjects:	Q Science > QH Natural history > QH301 Biology
Divisions:	Biological and Environmental Sciences (from Sep 19)
Date of acceptance:	27 March 2025
Date Deposited:	24 Jun 2025 10:56
Last Modified:	24 Jun 2025 10:56
DOI or ID number:	10.24377/LJMU.t.00026152
Supervisors:	Wilkinson, C, Frowd, C and Shrimpton, S
URI:	https://researchonline.ljmu.ac.uk/id/eprint/26152

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