Redesigning photo-ID to improve unfamiliar face matching performance

David White, A. Mike Burton, Rob Jenkins, Richard I. Kemp

Research output: Contribution to journalArticle

40 Citations (Scopus)
13 Downloads (Pure)

Abstract

Viewers find it difficult to match photos of unfamiliar faces for identity. Despite this, the use of photographic ID is widespread. In this study we ask whether it is possible to improve face matching performance by replacing single photographs on ID documents with multiple photos or an average image of the bearer. In three experiments we compare photo-to-photo matching with photo-to-average matching (where the average is formed from multiple photos of the same person) and photo-to-
array matching (where the array comprises separate photos of the same person). We consistently find an accuracy advantage for average images and photo arrays over single photos, and show that this improvement is driven by performance in match trials. In the final experiment, we find a benefit of four-image arrays relative to average images for unfamiliar faces, but not for familiar faces. We propose that conventional photo-ID format can be improved upon, and discuss this finding in the context of face recognition more generally.
Original languageEnglish
Pages (from-to)166-173
Number of pages8
JournalJournal of Experimental Psychology: Applied
Volume20
Issue number2
DOIs
Publication statusPublished - Jun 2014

Keywords

  • face recognition
  • unfamiliar face matching
  • identity verification
  • facial image comparison
  • image averaging

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