Research on a face recognition algorithm based on 3D face data and 2D face image matching

Abstract

Under the condition of weak light or no light, the recognition accuracy of the mature 2D face recognition technology decreases sharply. In this paper, a face recognition algorithm based on the matching of 3D face data and 2D face images is proposed. Firstly, 3D face data is reconstructed from the 2D face in the database based on the 3DMM algorithm, and the face depth image is obtained through orthogonal projection. Then, the average curvature map of the face depth image is used to enhance the data of the depth image. Finally, an improved residual neural network based on the depth image and curvature is designed to compare the scanned face with the face in the database. The method proposed in this paper is tested on the 3D face data in three public face datasets (Texas 3DFRD, FRGC v2.0, and Lock3DFace), and the recognition accuracy is 84.25%, 83.39%, and 78.24%, respectively.