Skip to main content

Fully Automatic Facial Deformation Transfer.

Bian, S., Zheng, A., Gao, L., Maguire, G., Kokke, W., Macey, J., You, L. and Zhang, J. J., 2019. Fully Automatic Facial Deformation Transfer. Symmetry, 12, 27.

Full text available as:

symmetry-12-00027-v2.pdf - Published Version
Available under License Creative Commons Attribution.


DOI: 10.3390/sym12010027


Facial Animation is a serious and ongoing challenge for the Computer Graphic industry. Because diverse and complex emotions need to be expressed by different facial deformation and animation, copying facial deformations from existing character to another is widely needed in both industry and academia, to reduce time-consuming and repetitive manual work of modeling to create the 3D shape sequences for every new character. But transfer of realistic facial animations between two 3D models is limited and inconvenient for general use. Modern deformation transfer methods require correspondences mapping, in most cases, which are tedious to get. In this paper, we present a fast and automatic approach to transfer the deformations of the facial mesh models by obtaining the 3D point-wise correspondences in the automatic manner. The key idea is that we could estimate the correspondences with different facial meshes using the robust facial landmark detection method by projecting the 3D model to the 2D image. Experiments show that without any manual labelling efforts, our method detects reliable correspondences faster and simpler compared with the state-of-the-art automatic deformation transfer method on the facial models.

Item Type:Article
Additional Information:Accepted: 17 December 2019; Published: 21 December 2019
Uncontrolled Keywords:face landmark detection; orthographic projection; point-wise correspondences; automatic deformation transfer
Group:Faculty of Media & Communication
ID Code:33886
Deposited By: Symplectic RT2
Deposited On:21 Apr 2020 15:49
Last Modified:14 Mar 2022 14:21


Downloads per month over past year

More statistics for this item...
Repository Staff Only -