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3D reconstruction from a single image for a Chinese talking face

机译:从一张会说话的中国面孔的单一图像进行3D重建

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This paper proposes an automatic 3D reconstruction approach for a Chinese talking face by a generic model and a single image. Firstly, an improved color-based ASM method is used to detect the face area and get the 2D face feature points automatically from the given image, which is not restricted to full frontal one. Then, color information is used to correct the location of face feature points. Finally, after text mapping, a particular and realistic 3D face model is deformed from a generic model. Using ASM face feature points extraction and correction based on skin color model, the problem of side face information missing is successfully resolved. Depending on only one image and one generic model, the computing cost of memory and time is largely reduced. The 3D face reconstructed can be easily deformed to form different expressions and mouth shapes. Experiments show that this approach is fast and efficient and has an output of a lifelike Chinese talking face.
机译:本文提出了一种通过通用模型和单个图像来实现汉语谈话的自动三维重建方法。首先,使用改进的基于ASM方法来检测面部区域并自动从给定图像获取2D面特征点,这不限于完全正面。然后,颜色信息用于校正面部特征点的位置。最后,在文本映射之后,特定和现实的3D面部模型从通用模型变形。使用基于肤色模型的ASM面部特征点提取和校正,成功解决了侧面信息的问题。根据一个图像和一个通用模型,存储器和时间的计算成本在很大程度上。重建的3D面部可以容易地变形以形成不同的表达和口腔形状。实验表明,这种方法是快速有效的,并具有栩栩如生的中文谈话的产出。

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