Expressive facial animation from videos
Changwei Luo, Chen Jiang, Jun Yu, Zengfu Wang · 2014
We address the issue of synthesizing real-time expressive facial animation from videos. Given video footage of a person's face, some existing methods track a few facial landmarks to drive the virtual character. Compared with these methods, ours has the following characteristics. 1) We incorporate global texture into a constrained local model to increase the accuracy of facial tracking. 2) To animate a blenshape face model, facial tracking results as well as facial expression recognition results are used to estimate blendshape weights. Experimental results demonstrate that our method is effective for producing realistic expressive facial animations. Moreover, the method does not require facial markers or complex offline pre-processing, these properties make it very easy to use for ordinary users.