@article{cao2013d,
author = {Cao, Chen and Weng, Yanlin and Lin, Steve and Zhou, Kun},
title = {3D shape regression for real-time facial animation},
year = {2013},
month = {July},
abstract = {We present a real-time performance-driven facial animation system based on 3D shape regression. In this system, the 3D positions of facial landmark points are inferred by a regressor from 2D video frames of an ordinary web camera. From these 3D points, the pose and expressions of the face are recovered by fitting a user-specific blendshape model to them. The main technical contribution of this work is the 3D regression algorithm that learns an accurate, user-specific face alignment model from an easily acquired set of training data, generated from images of the user performing a sequence of predefined facial poses and expressions. Experiments show that our system can accurately recover 3D face shapes even for fast motions, non-frontal faces, and exaggerated expressions. In addition, some capacity to handle partial occlusions and changing lighting conditions is demonstrated.},
url = {http://approjects.co.za/?big=en-us/research/publication/3d-shape-regression-real-time-facial-animation/},
journal = {ACM Transactions on Graphics (TOG) - SIGGRAPH 2013 Conference Proceedings},
volume = {32},
number = {4},
}