Modified Heat Method using GMRES for Geodesic Distance

Sudhanshu Rawat, M. Biswas
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Abstract

The computation of geodesic distance has applications in a wide variety of fields. Several attempts have been made in the last decade to compute geodesic on curved surfaces by formulating a distance function for the whole mesh including the heat method by Keenan crane. The proposed method first creates a vector unit field with a gradient equal to the true geodesic function and then integrates the unit vector field over the surface. Integrating the unit vector field over the surface requires solving a Poisson equation, which consists of two sparse linear systems of equations. The heat method proposed by Keenan crane uses a direct solver to solve the Poisson equation which increases the total memory and time consumption of the original heat method and makes it unsuitable for large meshes. The proposed method uses the generalized minimal residual method (GMRES) for solving the set of sparse linear systems of equations generated. The use of an iterative solver not only significantly reduces the memory consumption but also computes geodesic distance in less time than the heat method for large meshes which makes the proposed method preferable for large meshes. The result shows that the proposed method can efficiently compute the geodesic distance for bigger mesh in less time than the heat method and Biconjugate gradient stabilized method with significantly reduced memory usage for considered mesh data.
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基于GMRES的测地距离修正热法
测地线距离的计算有着广泛的应用领域。在过去的十年中,人们已经尝试了几种方法来计算曲面上的测地线,其中包括Keenan crane的热法。该方法首先建立一个梯度等于真测地线函数的矢量单位场,然后在曲面上对单位矢量场进行积分。单位向量场在曲面上的积分需要求解一个泊松方程,该泊松方程由两个稀疏线性方程组组成。Keenan crane提出的热法采用直接求解器求解泊松方程,增加了原热法的总内存和时间消耗,不适用于大型网格。该方法采用广义最小残差法(GMRES)求解生成的稀疏线性方程组。迭代求解器的使用不仅大大减少了内存消耗,而且与热法相比,在更短的时间内计算出了大网格的测地距离,使该方法更适合于大网格。结果表明,与热法和双共轭梯度稳定法相比,该方法可以在更短的时间内有效地计算更大网格的测地线距离,并显著减少了所考虑网格数据的内存占用。
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