3D Face Reconstruction System From A Single Photo Based On Regression Neural Network. Issue 5 (2020)

• Record Type: Journal Article
• Authors: Ji, Yatai; Li, Keqiang; Wu, Huaiyu; Xiong, Gang; Shen, Zhen; Shang, Xiuqin; Xi, Bangwen
• Is Part Of: IFAC-PapersOnLine. Volume 53:Issue 5(2020)
• Page Start: 71
• Page End: 76
• Publication Date: 2020
• Subjects: face reconstruct -- 3DMM -- 3DDFA -- regression network; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2021.04.213
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: 3D human face modeling is one of the most popular research directions in the field of computer stereo vision. On the one hand, the complex physiological structure of human face as well as various expressions and attitude changes bring great challenges to three-dimensional modeling, which makes the modeling method of human face have high research value and reference significance. On the other hand, 3D face reconstruction has a broad application prospect, and the application demand attracts more researchers to invest in it. Based on the 3DMM and 3DDFA method, this paper utilizes regression neural network to realize end-to-end face reconstruction. After that, we build a visualization program with the training model to realize face modeling based on a single face image of any pose or expression. It's a 3D face reconstruction system which has functions such as face alignment, face rotation and so on.