Facial recognition of identical twins

Abstract

Biometric identification systems must be able to distinguish between individuals even in situations where the bio metric signature may be similar, such as in the case of identical twins. This paper presents experiments done in facial recognition using data from a set of images of twins. This work establishes the current state of facial recognition in regards to twins and the accuracy of current state-of-the art programs in distinguishing between identical twins using three commercial face matchers, Cognitec 8.3.2.0, VeriLook 4.0, and PittPatt 4.2.1 and a baseline matcher employing Local Region PCA. Overall, it was observed that Cognitec had the best performance. All matchers, how ever, saw degradation in performance compared to an experiment where the ability to distinguish unrelated persons was assessed. In particular, lighting and expression seemed to have affected performance the most.