By Zhen Wen

ISBN-10: 1402080476

ISBN-13: 9781402080470

ISBN-10: 1402080484

ISBN-13: 9781402080487

ISBN-10: 1441954635

ISBN-13: 9781441954633

3D Face Processing: Modeling, research and Synthesis introduces the frontiers of 3D face processing innovations. It stories present 3D face processing recommendations, together with ideas 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 traditional facial movement, in addition to face visual appeal adaptations as a result of illumination and sophisticated movement. Then the authors follow the framework to stand monitoring, expression popularity and face avatar for HCI interface. They finish this e-book 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 desktop interplay and video surveillance. It includes a entire survey on current face processing innovations, that may function a reference for college students and researchers. It additionally covers in-depth dialogue on face movement research and synthesis algorithms, so one can 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)

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7(c) by labelling them via a GUI. Then, image warping technique is used to interpolate the correspondence in the remaining part. Note that the correspondences are based on only 2D facial feature locations, because only one image of a face is used in the GUI. g. , 2004]) to automate this step. The second step is to derive movements of facial surface points that are not sampled by markers in MUs. This is essentially a signal re-sampling problem, for which an interpolation-based method is usually used.

In the future, we plan to detect these feature locations automatically such that the whole fitting could be automatic. 1. Typical tracked frames and corresponding animated face models. (a): The input image frames. (b): The tracking results visualized by yellow mesh overlayed on input images. (c): The front views of the face model animated using tracking results. (d): The side views of the face model animated using tracking results. In each row, the first image corresponds to neutral face. Geometric Model-based 3D face tracking 37 In the current system, we use the holistic MUs derived in Section 3 of Chapter 3.

Then, the adjustment is done by moving the markers of the learned MUs to their corresponding positions on the new face. 7(c) by labelling them via a GUI. Then, image warping technique is used to interpolate the correspondence in the remaining part. Note that the correspondences are based on only 2D facial feature locations, because only one image of a face is used in the GUI. g. , 2004]) to automate this step. The second step is to derive movements of facial surface points that are not sampled by markers in MUs.

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3D Face Processing: Modeling, Analysis and Synthesis (The International Series in Video Computing) by Zhen Wen


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