Next Article in Journal
Research on the Detection Method of Implicit Self Symmetry in a High-Level Semantic Model
Previous Article in Journal
Skyrmion Crystals and Phase Transitions in Magneto-Ferroelectric Superlattices: Dzyaloshinskii–Moriya Interaction in a Frustrated J1J2 Model
Open AccessArticle

Fully Automatic Facial Deformation Transfer

1
The National Centre for Computer Animation, Bournemouth University, Poole BH12 5BB, UK
2
Humain Ltd., Belfast BT1 2LA, UK
3
Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
4
Belfast School of Art, Ulster University, York St, Belfast BT15 1ED, UK
*
Author to whom correspondence should be addressed.
Symmetry 2020, 12(1), 27; https://doi.org/10.3390/sym12010027
Received: 21 November 2019 / Revised: 13 December 2019 / Accepted: 17 December 2019 / Published: 21 December 2019
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. View Full-Text
Keywords: face landmark detection; orthographic projection; point-wise correspondences; automatic deformation transfer face landmark detection; orthographic projection; point-wise correspondences; automatic deformation transfer
Show Figures

Graphical abstract

MDPI and ACS Style

Bian, S.; Zheng, A.; Gao, L.; Maguire, G.; Kokke, W.; Macey, J.; You, L.; Zhang, J.J. Fully Automatic Facial Deformation Transfer. Symmetry 2020, 12, 27.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop