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首页> 外文期刊>IEEE Transactions on Pattern Analysis and Machine Intelligence >Analysis and synthesis of facial image sequences using physical and anatomical models
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Analysis and synthesis of facial image sequences using physical and anatomical models

机译:使用物理和解剖模型分析和合成面部图像序列

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摘要

An approach to the analysis of dynamic facial images for the purposes of estimating and resynthesizing dynamic facial expressions is presented. The approach exploits a sophisticated generative model of the human face originally developed for realistic facial animation. The face model which may be simulated and rendered at interactive rates on a graphics workstation, incorporates a physics-based synthetic facial tissue and a set of anatomically motivated facial muscle actuators. The estimation of dynamical facial muscle contractions from video sequences of expressive human faces is considered. An estimation technique that uses deformable contour models (snakes) to track the nonrigid motions of facial features in video images is developed. The technique estimates muscle actuator controls with sufficient accuracy to permit the face model to resynthesize transient expressions.
机译:为了估计和重新合成动态面部表情,提出了一种分析动态面部图像的方法。该方法利用了最初为逼真的面部动画开发的复杂人脸生成模型。可以在图形工作站上以交互速率进行仿真和渲染的面部模型,包括基于物理的合成面部组织和一组解剖学驱动的面部肌肉促动器。考虑从表达性人脸的视频序列估计动态面部肌肉收缩。开发了一种估计技术,该技术使用可变形轮廓模型(蛇形)来跟踪视频图像中人脸特征的非刚性运动。该技术以足够的精度估算肌肉致动器控制,以允许面部模型重新合成瞬时表情。

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