SPARE:用于鲁棒非刚性3D配准的对称点到平面距离。

IF 18.6
Yuxin Yao, Bailin Deng, Junhui Hou, Juyong Zhang
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引用次数: 0

摘要

现有的基于优化的非刚性配准方法通常基于源表面和目标表面上对应点对之间的点对点或点对平面距离来最小化对准误差度量。然而,这些度量可能导致缓慢的收敛或细节的丢失。在本文中,我们提出了SPARE,一种利用对称点到平面距离进行鲁棒非刚性配准的新公式。对称的点到平面距离依赖于对应点的位置和法线,从而更精确地逼近底层几何,并且可以达到比现有方法更高的精度。为了有效地解决这一优化问题,我们引入了一个尽可能刚性的调节项来估计变形法线,并提出了一个使用最大化-最小化策略的交替最小化求解器。此外,为了有效地初始化求解器,我们结合了基于变形图的粗对齐,提高了配准质量和效率。大量的实验表明,该方法大大提高了非刚性配准问题的精度,并保持了较高的求解效率。该代码可在https://github.com/yaoyx689/spare上公开获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SPARE: Symmetrized Point-to-Plane Distance for Robust Non-Rigid 3D Registration.

Existing optimization-based methods for non-rigid registration typically minimize an alignment error metric based on the point-to-point or point-to-plane distance between corresponding point pairs on the source surface and target surface. However, these metrics can result in slow convergence or a loss of detail. In this paper, we propose SPARE, a novel formulation that utilizes a symmetrized point-to-plane distance for robust non-rigid registration. The symmetrized point-to-plane distance relies on both the positions and normals of the corresponding points, resulting in a more accurate approximation of the underlying geometry and can achieve higher accuracy than existing methods. To solve this optimization problem efficiently, we introduce an as-rigid-as-possible regulation term to estimate the deformed normals and propose an alternating minimization solver using a majorization-minimization strategy. Moreover, for effective initialization of the solver, we incorporate a deformation graph-based coarse alignment that improves registration quality and efficiency. Extensive experiments show that the proposed method greatly improves the accuracy of non-rigid registration problems and maintains relatively high solution efficiency. The code is publicly available at https://github.com/yaoyx689/spare.

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