Automatic Reconstruction of Dense 3D Face Point Cloud with a Single Depth Image

Human face analysis is the basis for many other computer vision tasks, such as camera surveillance, entrance authorization and age estimation. With 3D face models, the vision task based on facial analysis can usually achieve a higher accuracy than the 2D cases since it provides more information with the additional dimension. However, most existing 3D face reconstruction methods suffer from complicated processing and high computation. This paper presents a novel method that simplifies the 3D face reconstruction process with only one shot of Kinect data. The output of the system is a high density of 3D face point cloud with smoother surface. This provides rich details of the human face for other computer vision tasks. Experiments with real world data show promising results using the proposed method.