Constructing faces from memory: the impact of image likeness and prototypical representations

Research suggests that memory for unfamiliar faces is pictorial in nature, with recognition negatively affected by changes to image-specific information such as head pose, lighting and facial expression. Further, within-person variation causes some images to resemble a subject more than others. Here, the purpose of this paper is to explore the impact of target-image choice on face construction using a modern evolving type of composite system, EvoFIT.

Participants saw an unfamiliar target identity and then created a single composite of it the following day with EvoFIT by repeatedly selecting from arrays of faces with “breeding”, to “evolve” a face. Targets were images that had been previously categorised as low, medium or high likeness, or a face prototype comprising averaged photographs of the same individual.

Identification of composites of low likeness targets was inferior but increased as a significant linear trend from low to medium to high likeness. Also, identification scores decreased when targets changed by pose and expression, but not by lighting. Similarly, composite identification from prototypes was more accurate than those from low likeness targets, providing some support that image averages generally produce more robust memory traces.

The results emphasise the potential importance of matching a target's pose and expression at face construction; also, for obtaining image-specific information for construction of facial-composite images, a result that would appear to be useful to developers and researchers of composite software.

This current project is the first of its kind to formally explore the potential impact of pictorial properties of a target face on identifiability of faces created from memory. The design followed forensic practices as far as is practicable, to allow good generalisation of results.