Familiarity effects in the construction of facial-composite images using modern software systems

We investigate the effect of target familiarity on the construction of facial composites, as used by law enforcement to locate criminal suspects. Two popular software construction methods were investigated. Participants were shown a target face that was either familiar or unfamiliar to them and constructed a composite of it from memory using a typical 'feature' system, involving selection of individual facial features, or one of the newer 'holistic' types, involving repeated selection and breeding from arrays of whole faces. This study found that composites constructed of a familiar face were named more successfully than composites of an unfamiliar face; also, naming of composites of internal and external features was equivalent for construction of unfamiliar targets, but internal features were better named than the external features for familiar targets. These findings applied to both systems, although benefit emerged for the holistic type due to more accurate construction of internal features and evidence for a whole-face advantage. STATEMENT OF RELEVANCE: This work is of relevance to practitioners who construct facial composites with witnesses to and victims of crime, as well as for software designers to help them improve the effectiveness of their composite systems.