@article{LIU2007, 
author = {Yanghua LIU and Guangyou XU},
title = {Personalized Multi-View Face Animation with Lifelike Textures},
year = {2007},
journal = {Tsinghua Science and Technology},
volume = {12},
number = {1},
pages = {51-57},
keywords = {face animation, point distribution model (PDM), texture, multi-view},
url = {https://www.sciopen.com/article/10.1016/S1007-0214(07)70008-1},
doi = {10.1016/S1007-0214(07)70008-1},
abstract = {Realistic personalized face animation mainly depends on a picture-perfect appearance and natural head rotation. This paper describes a face model for generation of novel view facial textures with various realistic expressions and poses. The model is achieved from corpora of a talking person using machine learning techniques. In face modeling, the facial texture variation is expressed by a multi-view facial texture space model, with the facial shape variation represented by a compact 3-D point distribution model (PDM). The facial texture space and the shape space are connected by bridging 2-D mesh structures. Levenberg-Marquardt optimization is employed for fine model fitting. Animation trajectory is trained for smooth and continuous image sequences. The test results show that this approach can achieve a vivid talking face sequence in various views. Moreover, the animation complexity is significantly reduced by the vector representation.}
}