3D face recognition using image decomposition and POEM descriptor

This article presents a novel algorithm for automatic 3D face recognition, which is robust to facial expression alterations, missing data, and outliers. This algorithm is divided into three main components: First, the 3D face scan is decomposed into structure–texture images. Second, feature vectors are extracted from each component. Third, a postprocessing is applied to deal with the outlier embedded in a feature. The proposed technique was tested on two public datasets (i.e., Gavab and Bosphorus). Experimental testing shows that our proposed methods can increase facial recognition performance, as compared to relevant state-of-the-art methods.