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Robust Non-rigid Registration Algorithm Based on Local Afflne Registration

机译：基于局部仿射配准的鲁棒非刚性配准算法

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摘要

Aiming at the problem that the traditional point set non-rigid registration algorithm has low precision and slow convergence speed for complex local deformation data, this paper proposes a robust non-rigid registration algorithm based on local affine registration. The algorithm uses a hierarchical iterative method to complete the point set non-rigid registration from coarse to fine. In each iteration, the sub data point sets and sub model point sets are divided and the shape control points of each sub point set are updated. Then we use the control point guided affine ICP algorithm to solve the local affine transformation between the corresponding sub point sets. Next, the local affine transformation obtained by the previous step is used to update the sub data point sets and their shape control point sets. When the algorithm reaches the maximum iteration layer A', the loop ends and outputs the updated sub data point sets. Experimental results demonstrate that the accuracy and convergence of our algorithm are greatly improved compared with the traditional point set non-rigid registration algorithms.
机译：针对传统的点集非刚性配准算法对复杂的局部变形数据精度低，收敛速度慢的问题，提出了一种基于局部仿射配准的鲁棒非刚性配准算法。该算法使用分层迭代方法来完成从粗糙到精细的点集非刚性配准。在每次迭代中，将子数据点集和子模型点集进行划分，并更新每个子点集的形状控制点。然后，我们使用控制点引导仿射ICP算法来求解相应子点集之间的局部仿射变换。接下来，通过上一步获得的局部仿射变换用于更新子数据点集及其形状控制点集。当算法达到最大迭代层A'时，循环结束并输出更新的子数据点集。实验结果表明，与传统的点集非刚性配准算法相比，该算法的准确性和收敛性得到了很大的提高。

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