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Integrating Surface Normal Vectors Using Fast Marching Method

机译:使用快速行进方法集成表面普通向量

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Integration of surface normal vectors is a vital component in many shape reconstruction algorithms that require integrating surface normals to produce their final outputs, the depth values. In this paper, we introduce a fast and efficient method for computing the depth values from surface normal vectors. The method is based on solving the Eikonal equation using Fast Marching Method. We introduce two ideas. First, while it is not possible to solve for the depths Z directly using Fast Marching Method, we solve the Eikonal equation for a function W of the form W = Z + λ f. With appropriately chosen values for λ, we can ensure that the Eikonal equation for W can be solved using Fast Marching Method. Second, we solve for W in two stages with two different λ values, first in a small neighborhood of the given initial point with large λ, and then for the rest of the domain with a smaller λ. This step is needed because of the finite machine precision and rounding-off errors. The proposed method is very easy to implement, and we demonstrate experimentally that, with insignificant loss in precision, our method is considerably faster than the usual optimization method that uses conjugate gradient to minimize an error function.
机译:表面正常向量的集成是许多形状重建算法中的重要组成部分,需要集成表面法线以产生它们的最终输出,深度值。在本文中,我们介绍了一种快速有效的方法,用于从表面普通向量计算深度值。该方法基于使用快速行进方法解决eikonal方程。我们介绍了两个想法。首先,虽然不可能使用快速游行方法直接解决深度Z,但是我们解决了形式W = Z +λf的函数W的eikonal方程。 With appropriately chosen values for λ, we can ensure that the Eikonal equation for W can be solved using Fast Marching Method.其次,我们用两个不同λ值的两个阶段来解决w,首先在给定初始点的小邻域中,具有大λ,然后用于域的其余域,具有较小的λ。由于有限的机器精度和舍入误差,需要此步骤。所提出的方法非常容易实现,我们通过实验证明,精确的微不足道的损失,我们的方法比使用共轭梯度最小化误差功能的通常优化方法更快。

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