Learning-based fully 3D face reconstruction from a single image

Xiaoping Hu; Ying Wang; Feiyun Zhu; Chunhong Pan

ICASSP 2016accepted0 citations

Learning-based fully 3D face reconstruction from a single image

Xiaoping Hu, Ying Wang, Feiyun Zhu, Chunhong Pan

Abstract

This paper presents an algorithm for fully reconstructing a 3D face from a single image. This task is still highly challenging as most current methods only care about the frontal face, ignoring side face, such as the neck, ears etc. In our algorithm, to get the more detailed texture, we deal with the shape reconstruction and texture recovery respectively. For shape, we estimate the deformation of the 3D model by a set of feature points. For texture, due to the similar facial structure, we divide the full texture into patches and show how sparse learning model can be used to fully recover the texture of the 3D face. Extensive experiment results on the CMU-PIE database and images downloaded from the Internet demonstrate that our method outperforms the state-of-the-art methods.

BibTeX

@inproceedings{icassp2016_learningbasedful,
  title = {Learning-based fully 3D face reconstruction from a single image},
  author = {Xiaoping Hu and Ying Wang and Feiyun Zhu and Chunhong Pan},
  booktitle = {ICASSP 2016},
  year = {2016}
}