@inproceedings{xin2005automatic,
author = {Xin, Le and Wang, Qiang and Tao, Jianhua and Tang, Xiaoou and Tan, Tieniu and Shum, Harry},
title = {Automatic 3D Face Modeling from Video},
booktitle = {IEEE ICCV},
year = {2005},
month = {October},
abstract = {In this paper, we develop an efficient technique for fully automatic recovery of accurate 3D face shape from videos captured by a low cost camera. The method is designed to work with a short video containing a face rotating from frontal view to profile view. The whole approach consists of three components. First, automatic initialization is performed in the first frame with approximately frontal face. Then, to handle the case of low quality image captured by low cost camera, the 2D feature matching, head poses and underlying 3D face shape are estimated and refined iteratively in an efficient way based on image sequence segmentation. Finally, to take advantage of the sparse structure of the proposed algorithm, sparse bundle adjustment technique is further employed to speed up the computation. We demonstrate the accuracy and robustness of the algorithm using a set of experiments.},
url = {http://approjects.co.za/?big=en-us/research/publication/automatic-3d-face-modeling-from-video/},
edition = {IEEE ICCV},
}