A New Approach for 2D-3D Heterogeneous Face Recognition

Abstract

This paper proposes a novel scheme for face recognition from visible images to depth images. In our proposed technique, we adopt Partial Least Square (PLS) to handle correlation mapping between 2D to 3D. A considerable performance improvement is observed compared to using Canonical Correlation Analysis (CCA). To further improve the performance, a fusion scheme based on PLS and CCA is advocated. We evaluate the advocated approach on a popular face dataset-FRGCV2.0. Experimental results demonstrate that the proposed scheme is an effective approach to perform 2D-3D face recognition.