By Zhen Wen
3D Face Processing: Modeling, research and Synthesis introduces the frontiers of 3D face processing strategies. It studies present 3D face processing options, together with options for 3D face geometry modeling; 3D face movement modeling; and 3D face movement monitoring and animation. Then it discusses a unified framework for face modeling, research and synthesis. during this framework, the authors current new tools for modeling complicated normal facial movement, in addition to face visual appeal adaptations because of illumination and refined movement. Then the authors practice the framework to stand monitoring, expression reputation and face avatar for HCI interface. They finish this ebook with reviews on destiny paintings within the 3D face processing framework. 3D Face Processing: Modeling, research and Synthesis will curiosity these operating in face processing for clever human laptop interplay and video surveillance. It encompasses a entire survey on latest face processing innovations, that can function a reference for college kids and researchers. It additionally covers in-depth dialogue on face movement research and synthesis algorithms, in order to profit extra complicated graduate scholars and researchers.
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Extra info for 3D Face Processing: Modeling, Analysis and Synthesis (The International Series in Video Computing)
B): Texture map. 3. Feature points defined on texture map. We define thirty-five facial feature points on the face surface of the generic head model. If we unfold the face component of the head model onto 2D, those feature points triangulate the face mesh into several local patches. 3. The system calculates 16 3D FACE PROCESSING: MODELING, ANALYSIS AND SYNTHESIS the 2D positions of the remaining face mesh vertices on the range map by deforming the local patches based on the range data. By collecting the range information according to the positions of the vertices on the range map, the 3D facial geometry is decided.
The generic face model. (a): Shown as wire-frame model. (b): Shown as shaded model. The generic face model in the iFACE system consists of nearly all the head components such as face, eyes, teeth, ears, tongue, and etc. The surfaces of the components are approximated by triangular meshes. There are 2240 vertices and 2946 triangles. The tongue component is modeled by a Non-Uniform 15 3D Face Modeling Rational B-Splines (NURBS) model which has 63 control points. 1. 2 Personalized face model In iFACE, the process of making a personalized face model is nearly automatic with only a few manual adjustments necessary.
2001, Reveret and Essa, 2001]. Then, arbitrary complex face deformation can be approximated by a linear combination of just a few basis vectors. , 2001b, Reveret and Essa, 2001]. Furthermore, facial deformation is known to be localized. To learn a localized subspace representation of facial deformation, Non-negative Matrix Factorization (NMF) [Lee and Seung, 1999] could be used. , 2001]. In this chapter, we describe how NMF may help to learn a parts-based facial deformation model. The advantage of a parts-based model is its flexibility in local facial motion analysis and synthesis.