{"title":"A physically-based model with adaptive refinement for facial animation","authors":"Yu Zhang, E. Prakash, E. Sung","doi":"10.1109/CA.2001.982374","DOIUrl":null,"url":null,"abstract":"The paper presents a physically-based 3D facial model based on anatomical knowledge for facial expression animation. The facial model incorporates a physically-based approximation to facial skin and a set of anatomically-motivated facial muscles. The skin model is established through the use of a mass-spring system with nonlinear springs which simulate the elastic-dynamics of a real facial skin. Muscle models are developed to emulate facial muscle contraction. Lagrangian mechanics governs the dynamics, dictating the deformation of facial surface in response to muscular forces. We show that when surface regions are influenced by the large muscular force, the local deformation becomes inaccurate. The conventional method to deal with this problem is using a fine network, but it also increases the cost of computation. We therefore present an approach to adaptively refine the mass-spring facial model to a required accuracy. It generates more pleasing results at low computational expense.","PeriodicalId":244191,"journal":{"name":"Proceedings Computer Animation 2001. Fourteenth Conference on Computer Animation (Cat. No.01TH8596)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Computer Animation 2001. Fourteenth Conference on Computer Animation (Cat. No.01TH8596)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CA.2001.982374","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 19
Abstract
The paper presents a physically-based 3D facial model based on anatomical knowledge for facial expression animation. The facial model incorporates a physically-based approximation to facial skin and a set of anatomically-motivated facial muscles. The skin model is established through the use of a mass-spring system with nonlinear springs which simulate the elastic-dynamics of a real facial skin. Muscle models are developed to emulate facial muscle contraction. Lagrangian mechanics governs the dynamics, dictating the deformation of facial surface in response to muscular forces. We show that when surface regions are influenced by the large muscular force, the local deformation becomes inaccurate. The conventional method to deal with this problem is using a fine network, but it also increases the cost of computation. We therefore present an approach to adaptively refine the mass-spring facial model to a required accuracy. It generates more pleasing results at low computational expense.