Robust 3D Local SIFT Features for 3D Face Recognition

摘要

In this paper, a robust 3D local SIFT feature is proposed for 3D face recognition. For preprocessing the original 3D face data, facial regional segmentation is first employed by fusing curvature characteristics and shape band mechanism. Then, we design a new local descriptor for the extracted regions, called 3D local Scale-Invariant Feature Transform (3D LSIFT). The key point detection based on 3D LSIFT can effectively reflect the geometric characteristic of 3D facial surface by encoding the gray and depth information captured by 3D face data. Then, 3D LSIFT descriptor extends to describe the discrimination on 3D faces. Experimental results based on the common international 3D face databases demonstrate the higher-qualified performance of our proposed algorithm with effectiveness, robustness, and universality.