By Zhen Wen
3D Face Processing: Modeling, research and Synthesis introduces the frontiers of 3D face processing ideas. It experiences current 3D face processing suggestions, 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 equipment for modeling complicated usual facial movement, in addition to face visual appeal diversifications because of illumination and sophisticated movement. Then the authors observe the framework to stand monitoring, expression popularity 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 incorporates a entire survey on latest face processing options, which could function a reference for college kids and researchers. It additionally covers in-depth dialogue on face movement research and synthesis algorithms, to be able to profit extra complex graduate scholars and researchers.
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Extra info for 3D Face Processing: Modeling, Analysis and Synthesis (The International Series in Video Computing)
Then, in Section 2, we introduce the motion capture database used in our framework. Section 3 and 4 present our methods for learning holistic and parts-based spatial geometric facial motion models, respectively. Section 5 introduces how we apply the learned models to arbitrary face mesh. Finally, in Section 6, we brief describe the temporal facial motion modeling in our framework. 1. Previous Work Since the pioneering work of Parke [Parke, 1972] in the early 70’s, many techniques have been investigated to model facial deformation for 3D face tracking and animation.
To approximate the space of facial deformation, people proposed linear subspaces based on Facial Action Coding System (FACS) [Essa and Pentland, 1997, Tao and Huang, 1999]. FACS [Ekman and Friesen, 1977] describes arbitrary facial deformation as a combination of Action Units (AUs) of a face. Because AUs are only defined qualitatively, and do not contain temporal information, they are usually manually customized for computation. Brand [Brand, 2001] used lowlevel image motion to learn a linear subspace model from raw video.
1998]. 1 Parameterized geometric models B-Spline curves Blake et al. , 1993] propose parametric B-spline curves for contour tracking. The tracking problem is to estimate the control points of the B-spline curve so that the B-spline curve matches the contour being tracked as closely as possible. However, without global constraints, B-spline curves tend to match contours locally, resulting in wrong matching among contour points. , 1995]. Therefore, it prevents generating physically impossible curves.