Identity Verification for Attendees of Large-scale Events Using Face Recognition of Selfies Taken with Smartphone Cameras

Abstract

This paper proposes an identity-verification system for attendees of large-scale events using face recognition from selfies taken with smartphone cameras. Such a system has been required to prevent illegal resale such as ticket scalping. The problem in verifying ticket holders is how to simultaneously verify identities efficiently and prevent individuals from impersonating others at a large-scale event at which tens of thousands of people participate. We developed two ticket ID systems for identifying the purchaser and holder of a ticket that uses two face-recognition systems, i.e., tablet-based and non-stop face-recognition systems that require ID equipment such as a tablet terminal with a camera, card reader, and ticket-issuing printer. Since these systems were proven effective for preventing illegal resale by verifying attendees at large concerts of popular music groups, they have been used at more than 100 concerts. However, simplifying the ID equipment is necessary from an operational view-point. It is also necessary to secure clear facial photos from a technical view-point of face-recognition accuracy because face recognition fails when unclear face photos are obtained, i.e., when individuals have their eyes closed, not looking directly forward, or have hair covering their faces. We proposed a system that uses attendees' selfies as input photos for face recognition, which simplifies ID equipment by only requiring smartphone cameras, enabling clear face photos to be obtained the allowing attendees to take their own photos. The system achieved 97.5% face-recognition accuracy in preliminary tests of 240 photos taken under various brightness and background conditions.