Improving Robustness of Ear Detection For Pose Variation

Abstract

An algorithm improving the robustness of an ear biometric system is proposed. In order to deal with pose variation rotated in depth, Gabor jets of different poses are estimated and used as training data for discriminant analysis based classifier. Experimental evaluations show the effectiveness of the proposed algorithm, and possibility of improving the robustness of single-view-based ear surveillance-system.