Download 3D Face Processing (The Kluwer International Series in Video by Ming-Hsuan Yang, Narendra Ahuja PDF

By Ming-Hsuan Yang, Narendra Ahuja

3D Face Processing: Modeling, research and Synthesis will curiosity these operating in face processing for clever human laptop interplay and video surveillance. It includes a accomplished survey on current face processing options, which could function a reference for college students and researchers. It additionally covers in-depth dialogue on face movement research and synthesis algorithms, in order to profit extra complex graduate scholars and researchers.

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Extra info for 3D Face Processing (The Kluwer International Series in Video Computing): Modeling, Analysis, and Synthesis

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But our formulation is easier in a sense that it can viewed as a natural extension of traditional key-framebased spline interpolation scheme, given the probability distribution of each key frame. 1 shows a synthetic example comparing conventional NURBS and our statistically weighted NURBS. The dots are samples of facial shapes. 1. terpolation. (a): Conventional NURBS interpolation. (b): Statistically weighted NURBS in- The dashed line connects centers of the states. The solid line is the generated facial deformation trajectory.

Subspace modeling: When the 3D face database includes more geometry variations, PCA may no longer be a good way to model the face geometry subspace. Other subspace learning methods, such as Independent Component Analysis (ICA) [Comon, 1994], local PCA [Kambhatla and Leen, 1997], need to explored the find better subspace representation. Illumination effects of texture model: The textures of the 3D face models also need to be collected to model the appearance variation, as in [Blanz and Vetter, 1999].

Because of the high complexity of natural facial motion, these models usually need extensive manual adjustments to achieve plausible facial deformation. 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.

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