Understanding Biometric Error
Principal Investigator: Stephen Elliott
Historically, biometric performance has relied on basic metrics such as FNMR and FMR, as well as Failure to Enroll, Failure to Acquire etc. As biometric deployments become widespread, and the number of people enrolled is in the millions, a 1% error rate is a significantly large number. A large part of our research portfolio is trying to understand this error, and providing new definitions and metrics. The goal of this research is to improve operational performance, design better systems (in line with the HBSI model), and to further the research communities understanding of biometric error.
Students: Greg Hales Mitch Mershon Kevin O'Conner Will Ott Benny Senjaya Adam Wamsley