Implications of Adult Facial Aging on Biometrics

Abstract

1.1 Statement of the problem Single features of the human face, facial components, as well as the human face taken as a whole may be viewed as a biometric tool for purposes of individual human identification. Using computer technology, automated face recognition (FR) systems have been created to match individual faces from print and digital photographs and video to faces of the same individual whose image is stored among many others in a computer database. One of the primary problems that arise with FR systems is how to contend with the passage of time and the resultant effects of facial aging. Enrolled, i.e. gallery, images become difficult to match against a query, i.e. probe, image as the time span between the gallery and the probe increases. Several researchers have highlighted this temporal performance degradation (Pentland & Choudhury, 2000; Phillips et al., 2000; Ricanek et al., 2006) .To meet this challenge, two approaches have been taken: (1) research what is known about adult age-related craniofacial morphological changes to better understand how to (2) synthetically age individuals from a facial image, or rather, develop workable artificial age progression techniques to anticipate how an individual’s facemay appear years down the road. In addition to probing the question of how a person’s face may age across the adult lifespan, other facial appearance questions have arisen, such as how might a person’s face change simply over the course of one day? Herein we present an overview of face aging, its implications on biometrics, specifically FR systems, and provide an example of our work via relaying results of experiments designed to measure facial age changes and artificially synthesize facial images, all in an effort to improve FR systems and ensure that facial features, when used as a biometric tool, are reliable, consistent, and accurate with replicable results.