Improved approach for 3D face characterization

Abstract

Representing and extracting good quality of facial feature extraction is an essential step in many applications, such as face recognition, pose normalization, expression recognition, human–computer interaction and face tracking. We are interested in the extraction of the pertinent features in 3D face. In this paper, we propose an improved algorithm for 3D face characterization. We propose novel characteristics based on seven salient points of the 3D face. We have used the Euclidean distances and the angles between these points. This step is highly important in 3D face recognition. Our original technique allows fully automated processing, treating incomplete and noisy input data. Besides, it is robust against holes in a meshed image and insensitive to facial expressions. Moreover, it is suitable for different resolutions of images. All the experiments have been performed on the FRAV3D and GAVAB databases.