SPARE: Symmetrized Point-to-Plane Distance for Robust Non-Rigid 3D Registration
Abstract
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.
Keywords
Cite
@article{arxiv.2405.20188,
title = {SPARE: Symmetrized Point-to-Plane Distance for Robust Non-Rigid 3D Registration},
author = {Yuxin Yao and Bailin Deng and Junhui Hou and Juyong Zhang},
journal= {arXiv preprint arXiv:2405.20188},
year = {2025}
}
Comments
Accepted to IEEE Transactions on Pattern Analysis and Machine Intelligence