Empirical Evaluations of a Single-view-based Ear Recognition when Rotated in Depth

Abstract

To deal with variations in poses that are rotated in depth, the authors have previously introduced a method where the Gabor jets of different poses are estimated and used as training data for a discriminant analysis-based classifier. To improve the viability of the authors' methods, experimental evaluations are conducted under realistic scenarios.