曲面配准的最优步非刚性ICP算法

Brian Amberg, S. Romdhani, T. Vetter
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引用次数: 714

摘要

我们展示了如何将ICP框架扩展到非刚性配准,同时保留了原始算法的收敛性。所得到的最佳步骤非刚性ICP框架允许使用不同的正则化,只要它们具有可调的刚度参数。配准循环在一系列减小的刚度权值上,并逐渐使模板向目标变形,恢复全局和局部变形的整个范围。为求给定刚度下的最优变形,采用最优迭代最近点步。初步对应是通过最近点搜索估计的。然后计算模板在这些固定对应下的最优变形量和主动刚度。之后,该过程继续通过从移位的模板顶点搜索找到新的对应关系。我们提出了一种使用局部仿射正则化的算法,该算法为每个顶点分配一个仿射变换,并使相邻顶点的变换差异最小化。结果表明,这种正则化方法可以准确有效地确定固定对应和固定刚度的最优变形。该方法适用于多种初始条件,并能鲁棒地处理缺失数据。使用合成示例和真实世界数据,将其定性和定量地与其他算法进行比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal Step Nonrigid ICP Algorithms for Surface Registration
We show how to extend the ICP framework to nonrigid registration, while retaining the convergence properties of the original algorithm. The resulting optimal step nonrigid ICP framework allows the use of different regularisations, as long as they have an adjustable stiffness parameter. The registration loops over a series of decreasing stiffness weights, and incrementally deforms the template towards the target, recovering the whole range of global and local deformations. To find the optimal deformation for a given stiffness, optimal iterative closest point steps are used. Preliminary correspondences are estimated by a nearest-point search. Then the optimal deformation of the template for these fixed correspondences and the active stiffness is calculated. Afterwards the process continues with new correspondences found by searching from the displaced template vertices. We present an algorithm using a locally affine regularisation which assigns an affine transformation to each vertex and minimises the difference in the transformation of neighbouring vertices. It is shown that for this regularisation the optimal deformation for fixed correspondences and fixed stiffness can be determined exactly and efficiently. The method succeeds for a wide range of initial conditions, and handles missing data robustly. It is compared qualitatively and quantitatively to other algorithms using synthetic examples and real world data.
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