Jobila Eigenmann – Assessing online EvoFit facial composite construction

When the suspect of a crime escapes, a way to identify them is with a facial composite system that accurately allows witnesses to produce recognizable composites or likenesses of the suspect. A self-administered online version of EvoFit has recently been developed to allow witnesses to create composites in their own homes, to reduce factors like stress and police resources. Research has shown that the standardized EvoFit in lab conditions yields more recognizable composites than EvoFit online (Frowd, et al., 2012). In this study, participants created composites of unfamiliar faces in two conditions- Experimenter Present (emulating the lab condition of the standardized program) and Experimenter Absent. The study aimed to determine if experimenter presence increases the perceived resemblance of a likeness, to optimize EvoFit Online to produce the same, if not more, percentage of accurate composites. Previous research with EvoFit has shown that experimenter presence increases the similarity of a composite and that the correct naming rate for EvoFit Online is surprisingly low (Martin et al., 2018). The results of the current study showed a marginal difference between the two conditions, where the Experimenter Absent condition had a higher average of correctly named composites (M= 5.20, SD ±4.49) than the Experimenter Present condition (M=4.81, SD ±2.90). However, no statistical significance was recorded, suggesting that in addition to experimenter presence, there may have been other factors that affected the resemblance of the composites, as for example, stress, in addition to flaws in the methodology.
Keywords: facial composite system, holistic processing, composite, likeness, EvoFit, target, feature-based systems.