A reconstruction method of 3D face model from front and side 2D face images using deep learning model

In this study, we focus on automatic three-dimensional (3D) face reconstruction from two-dimensional (2D) face images using a deep learning model. The conventional methods have been used to develop models that can reconstruct 3D faces from 2D images. However, for Japanese faces, the models cannot accurately reconstruct images vertical bar large errors occur in areas such as the nose and mouth vertical bar because most of the training data are foreigner's face images. To solve this problem, we proposed a method that uses not only a frontal 2D face image but also a side-view 2D face image for the 3D face reconstruction, and the resulting 3D model is a combination of two 3D reconstructed models, which are created from the frontal and side-view 2D face images using iterative closest point algorithm. As a result, the accuracy of the proposed method is better than the conventional method.