Caricaturing can improve facial expression recognition in low-resolution images and age-related macular degeneration

Jo Lane, Rachel A. Robbins, Emilie M.F. Rohan, Kate Crookes, Rohan W. Essex, Ted Maddess, Faran Sabeti, Jamie Lee Mazlin, Jessica Irons, Tamara Gradden, Amy Dawel, Nick Barnes, Xuming He, Michael Smithson, Elinor McKone

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)
61 Downloads (Pure)


Previous studies of age-related macular degeneration (AMD) report impaired facial expression recognition even with enlarged face images. Here, we test potential benefits of caricaturing (exaggerating how the expression's shape differs from neutral) as an image enhancement procedure targeted at mid- to high-level cortical vision. Experiment 1 provides proof-of-concept using normal vision observers shown blurred images as a partial simulation of AMD. Caricaturing significantly improved expression recognition (happy, sad, anger, disgust, fear, surprise) by ∼4%-5% across young adults and older adults (mean age 73 years); two different severities of blur; high, medium, and low intensity of the original expression; and all intermediate accuracy levels (impaired but still above chance). Experiment 2 tested AMD patients, running 19 eyes monocularly (from 12 patients, 67-94 years) covering a wide range of vision loss (acuities 6/7.5 to poorer than 6/360). With faces pre-enlarged, recognition approached ceiling and was only slightly worse than matched controls for high- and medium-intensity expressions. For low-intensity expressions, recognition of veridical expressions remained impaired and was significantly improved with caricaturing across all levels of vision loss by 5.8%. Overall, caricaturing benefits emerged when improvement was most needed, that is, when initial recognition of uncaricatured expressions was impaired.

Original languageEnglish
Article number18
Pages (from-to)1-22
Number of pages22
JournalJournal of Vision
Issue number6
Publication statusPublished - Jun 2019


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