Expression-invariant three-dimensional face reconstruction from a single image by facial expression generic elastic models

An efficient method for expression-invariant three-dimensional (3-D) face reconstruction from a frontal face image with a variety of facial expressions (FE) using the FE generic elastic model (GEM) is proposed. Three generic models are employed for FE modeling in the generic elastic model (GEM) framework, which are combined based on the similarity distance around the lips. Exclusively, FE-GEM demonstrated that it is more precisely able to estimate a 3-D model of a frontal face, attaining a more robust and better quality 3-D face reconstruction under a variety of FEs compared to the original GEM approach. It is tested on an available 3-D face database and its accuracy and robustness are demonstrated compared to the GEM approach under a variety of FEs. Also, the FE-GEM method is tested on available two-dimensional face databases and a new synthesized pose is generated from gallery images for handling pose variations in face recognition.