Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.jvlc.2005.10.002
Title: Anatomy-based face reconstruction for animation using multi-layer deformation
Authors: Zhang, Y. 
Sim, T. 
Tan, C.L. 
Sung, E.
Keywords: Anatomy-based model
Face reconstruction
Facial animation
Multi-layer deformation
Multi-layer skin/muscle/skull structure
Scanned data
Issue Date: 2006
Source: Zhang, Y., Sim, T., Tan, C.L., Sung, E. (2006). Anatomy-based face reconstruction for animation using multi-layer deformation. Journal of Visual Languages and Computing 17 (2) : 126-160. ScholarBank@NUS Repository. https://doi.org/10.1016/j.jvlc.2005.10.002
Abstract: This paper presents a novel multi-layer deformation (MLD) method for reconstructing animatable, anatomy-based human facial models with minimal manual intervention. Our method is based on adapting a prototype model with the multi-layer anatomical structure to the acquired range data in an "outside-in" manner: Deformation applied to the external skin layer is propagated along with the subsequent transformations to the muscles, with the final effect of warping the underlying skull. The prototype model has a known topology and incorporates a multi-layer structure hierarchy of physically based skin, muscles, and skull. In the MLD, a global alignment is first carried out to adapt the position, size, and orientation of the prototype model to align it with the scanned data based on measurements between a subset of specified anthropometric landmarks. In the skin layer adaptation, the generic skin mesh is represented as a dynamic deformable model which is subjected to internal force stemming from the elastic properties of the surface and external forces generated by input data points and features. A fully automated approach has been developed for adapting the underlying muscle layer which consists of three types of physically based facial muscle models. MLD deforms a set of automatically generated skull feature points according to the adapted external skin and muscle layers. The new positions of these feature points are then used to drive a volume morphing applied to the template skull model. We demonstrate our method by applying it to generate a wide range of different facial models on which various facial expressions are animated. © 2005 Elsevier Ltd. All rights reserved.
Source Title: Journal of Visual Languages and Computing
URI: http://scholarbank.nus.edu.sg/handle/10635/43140
ISSN: 1045926X
DOI: 10.1016/j.jvlc.2005.10.002
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