Evaluating the Feature Comparison Strategy for Forensic Face Identification

Face recognition is thought to rely on representations that encode holistic properties. Paradoxically, professional forensic examiners who identify unfamiliar faces by comparing facial images are trained to adopt a feature-by-feature comparison strategy. Here we tested the effectiveness of this strategy by asking participants to rate facial feature similarity prior to making same/different identity decisions to pairs of face images. Experiment 1 provided preliminary evidence that rating feature similarity improves unfamiliar face matching accuracy in novice participants. In Experiment 2, we found benefits of this procedure over and above rating similarity of personality traits and image quality parameters, suggesting that benefits are not solely attributable to general increases in attention. In Experiment 3, we then compared performance of trained forensic facial image examiners to novice participants, and found that examiners displayed: i) superior face matching accuracy; ii) smaller face inversion and feature inversion effects; and iii) feature ratings that were more diagnostic of identity. Further, aggregating feature ratings of multiple examiners produced perfect identity discrimination. Based on these quantitative and qualitative differences between experts and novices, we conclude that comparison based on local features confers specific benefits to trained forensic examiners.