Approximate gradient direction metric for face authentication

Abstract

In pattern recognition problems where the decision making is based on a measure of similarity, the choice of an appropriate distance metric significantly influences the performance and speed of the decision making process. We develop a novel metric which is an approximation of the successful Gradient Direction (GD) metric. The proposed metric is evaluated on a face authentication problem using the Banca database. It outperforms the standard benchmark, the normalised correlation. Although it is not as powerful as GD metric, it is ten times faster. © Springer-Verlag 2004.