ABSTRACT
There are multiple well-established situations in which humans' face recognition performance is poor, including for low-resolution images, other-race faces, and in older adult observers. Here we show that caricaturing faces-that is, exaggerating their appearance away from an average face-can provide a useful applied method for improving face recognition across all these circumstances. We employ a face-name learning task offering a number of methodological advantages (e.g., valid comparison of the size of the caricature improvement across conditions differing in overall accuracy). Across six experiments, we (a) extend previous evidence that caricaturing can improve recognition of low-resolution (blurred) faces; (b) show for the first time that caricaturing improves recognition and perception of other-race faces; and (c) show for the first time that caricaturing improves recognition in observers across the whole adult life span (testing older adults, M age = 71 years). In size, caricature benefits were at least as large where natural face recognition is poor (other-race, low resolution, older adults) as for the naturally best situation (own-race high-resolution faces in young adults). We discuss potential for practical applicability to improving face recognition in low-vision patients (age-related macular degeneration, bionic eye), security settings (police, passport control), eyewitness testimony, and prosopagnosia. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
