Facial Animation Based on 2D Shape Regression

We present a facial animation system for ordinary single-cameral videos based on 2D shape regression. Unlike some prior facial animation techniques, our system doesn’t need complex equipment. The system consists of firstly a Cascade Multi-Channel Convolutional Neural Network (CMC-CNN) model to accurately detect facial landmarks from 2D video frames. Based on these detected 2D points, the facial motion parameters, including the head pose and facial expressions, are recovered. Then the system animates a bone-driven 3D avatar with the facial motion parameters. Experiments show that our system can accurately detect facial landmarks and the animation results are visually plausible and similar to the user’s facial motion.