Confidence Based Gating of Multiple Face Authentication Experts

We address the problem of fusing experts employing diverse similarity measures in LDA face space. The gradient direction measure is reviewed and experimentally compared with the normalised correlation in two different conditions, when the face images are well registered and when the registration process is performed automatically. We show that by combining the gradient direction measure and normalised correlation using a confidence based gating, the resulting decision making scheme consistently outperforms the best method. The gating is based on a novel decision confidence measure proposed in the paper.