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Delaunay Triangulation based 3D Human Face Modeling from Uncalibrated Images

机译:基于Delaunay三角测量的基于Uncalbriated图像的3D人脸建模

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摘要

In this paper, we describe an algorithm for generating three dimensional models of human faces from uncalibrated images. Input images are taken by a camera generally with a small rotation around a single axis which may cause degenerate solutions during auto-calibration. We describe a solution to this problem by a priori assumptions on the camera. To generate a specify person's head, a generic human head model is deformed according to the 3D coordinates of points obtained by reconstructing the scene using images calibrated with our algorithm. The deformation process is based on a physical based massless spring model and it requires local retriangulation in the areas with high curvatures. This is achieved by locally applying Delaunay triangulation method. However, there may occur degeneracies in Delaunay triangulation such as encroaching of edges. We describe an algorithm for removing the degeneracies during triangulation by modifying the definition of the Delaunay cavity. This algorithm has also the effect of preserving the curvature in the face area. We have compared the models generated with our algorithm with the models obtained using cyber scanners. The RMS geometric error in these comparisons are less than 1.8 × 10{sup}(-2).
机译:在本文中,我们描述了一种用于从未校准图像产生三维模型的算法。输入图像由相机拍摄,通常围绕单个轴围绕旋转,这可能在自动校准期间导致退化的解决方案。我们通过相机上的先验假设来描述解决此问题的解决方案。为了生成指定人的头部,通用人头模型根据通过使用算法校准的图像重建场景而获得的点的3D坐标变形。变形过程基于基于物理的麻布弹簧模型,并且需要在具有高曲率的区域中的局部标记。这是通过局部应用Delaunay三角测量方法实现的。然而,在Delaunay三角测量中可能发生退化阶段,例如侵占边缘。通过修改Delaunay腔的定义,我们描述了一种用于在三角测量期间去除天赋的算法。该算法还具有保护曲率在面部区域中的效果。我们将使用我们的算法生成的模型与使用网络扫描仪获得的模型进行了比较。这些比较中的RMS几何误差小于1.8×10 {sup}( - 2)。

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