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High quality lip-sync animation for 3D photo-realistic talking head

机译:用于3D逼真的说话人头部的高质量口型同步动画

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We propose a new 3D photo-realistic talking head with high quality, lip-sync animation. It extends our prior high-quality 2D photo-realistic talking head to 3D. An a/v recording of a person speaking a set of prompted sentences with good phonetic coverage for ∼20-minutes is first made. We then use a 2D-to-3D reconstruction algorithm to automatically adapt a general 3D head mesh model to the person. In training, super feature vectors consisting of 3D geometry, texture and speech are augmented together to train a statistical, multi-streamed, Hidden Markov Model (HMM). The HMM is then used to synthesize both the trajectories of head motion animation and the corresponding dynamics of texture. The resultant 3D talking head animation can be controlled by the model predicted geometric trajectory while the articulator movements, e.g., lips, are rendered with dynamic 2D texture image sequences. Head motions and facial expression can also be separately controlled by manipulating corresponding parameters. In a real-time demonstration, the life-like 3D talking head can take any input text, convert it into speech and render lip-synced speech animation photo-realistically.
机译:我们提出了一种具有高质量,口型同步动画的新型3D逼真的讲话头。它将我们先前的高质量2D逼真的话音头部扩展到3D。首先录制一个语音提示集,语音提示覆盖20分钟左右的人的音像记录。然后,我们使用2D到3D重建算法来自动将通用3D头部网格模型适应人。在训练中,将由3D几何,纹理和语音组成的超特征向量一起增强,以训练统计的,多数据流的隐马尔可夫模型(HMM)。然后,将HMM用于合成头部运动动画的轨迹和相应的纹理动态。可以通过模型预测的几何轨迹来控制最终的3D讲话头动画,同时用动态2D纹理图像序列渲染咬合器运动(例如嘴唇)。头部动作和面部表情也可以通过操纵相应的参数来分别控制。在实时演示中,栩栩如生的3D对话头可以获取任何输入文本,将其转换为语音,并以逼真的方式渲染口型同步的语音动画。

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