Face matching as a majority: Getting the best from a crowd.

Abstract

For unfamiliar faces, deciding whether two photographs depict the same person or not can be difficult. One way to substantially improve accuracy is to defer to the 'wisdom of crowds' by aggregating responses across multiple individuals. However, there are several methods available for doing this. Here, we investigated performance in three tests of unfamiliar face matching. In all cases, we found that going with the option chosen by the majority of people provided the best approach. No benefit was found by weighting an option's popularity using average confidence, while choosing the 'surprisingly popular' option resulted in a sizeable decrease in accuracy. Therefore, rather than incorporating metacognitive judgements, we endorse a simple majority vote for this particular task.