A police video identification parade often contains one police suspect and (usually 8) other people who ressemble the suspect and are known-to-be-innocent, called fillers. Usually the fillers are selected from a large database of available images. How should identification officers choose fillers from the database to optimise eyewitness identification accuracy, while also ensuring parades are legally compliant?This research uses psychological theories of eyewitness memory and a series of experiments to predict and test how suspect-filler similarity influences eyewitness memory accuracy.
We will use a combination of methods to answer this question. We will build simulations based on models of memory, to predict how suspect-filler similarity influences witness memory accuracy. We will also conduct empirical experiments with large samples (N>8000) to test the predictions. In these experiments, participants acting as witness will view a simulated crime, and, after a brief delay, have to identify the culprit from a lineup. The lineups will differ in their filler compositions.