3D Face Model Reconstruction Based on a Single Unconstrained Image

• Main Authors: WU, ZI-LYNN, 吳梓麟
• Other Authors: SHIH, SHENG-WEN
• Format: Others
• Language: zh-TW
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/v6z565

碩士 === 國立暨南國際大學 === 資訊工程學系 === 107 === This thesis aims to reconstruct a 3D face model from a single unconstrained image. A 3D face reconstruction method is developed based on the method proposed by Wei et al. The face models used in this work are selected from the BP4D-Spontanous dataset, which contains high resolution color facial images and the corresponding 3D models of several human races in different facial expressions. The reconstruction method consists of camera parameters estimation, 3D reference model coefficients estimation, nonlinear optimization, texture mapping, and synthesis of occluded image regions. A new method to improve numerical stability in estimating camera parameters is proposed. The 3D reference model coefficients are re-parametrized so as to convert the original constrained optimization problem into an unconstrained one. Also, a skin-color-aware occluded region synthesis method is developed to reduce artifacts in the reconstructed texture map. The proposed method only cost 135.40 milliseconds to reconstruct a 3D face model from an input 2D facial image. Experiments show that the reconstructed 3D face model can be used to improve the face recognition accuracy for 0.02%.