Self-adaptive morphable model based multi-view non-cooperative 3D face reconstruction

Non-cooperative 3D face reconstruction is very significant in the area of intelligent security. According to non-cooperative 3D face reconstruction, the non-complete information fusion of multi-view face images can be realized to get a more complete face. This paper proposes a non-cooperative 3D face reconstruction method. A multimedia sensor network is employed to detect a person and get face images from different views. View-based active appearance models (View-based AAM) then helps to extract feature points and estimate probable pose angle. A new self-adaptive 3D morphable model based multi-view face geometry reconstruction method is designed to generate a 3D face model with particle swarm optimization (PSO). As the initial pose estimation is not accurate, particle swarm optimization is also used to regulate pose estimation results for optimizing 3D reconstruction result. “Mirror” strategy is employed to difine the invisible part of the face based on the mirror image of the visible part for texture mapping. Experiments have shown that the proposed method can achieve the non-cooperative 3D reconstruction efficaciously.