发表机构
Northwestern Polytechnical University（西北工业大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对薄片状文化遗产文物，提出一种几何约束的双向点云配准方法，通过语义预处理、PCA归一化和厚度感知约束解决旋转模糊与结构坍塌问题，实现可靠的非接触三维重建。
AI 中文摘要
薄片状文化遗产文物的非接触式三维重建面临显著的几何和配准挑战。由于这些文物易碎，无法悬挂或安装人工标记，因此需要独立采集其正面和背面表面。后续配准因共享几何特征数量有限以及显式物理约束的缺乏而变得困难，这可能导致迭代优化过程中的旋转模糊性、不稳定性和结构坍塌。为应对这些挑战，我们提出了一种专门针对薄片状文化遗产文物的几何约束双向点云配准方法。该方法整合了语义引导的预处理、基于主成分分析（PCA）的几何归一化以及厚度感知的配准策略。估计的物理厚度被纳入作为几何约束，以在配准过程中保持结构完整性。旋转模糊性通过评估一组有限的全局旋转假设来解决，每个假设使用点对平面迭代最近点（ICP）算法进行细化，并通过与厚度尺度一致的几何感知适应度准则选择最优变换。实验结果表明，所提出的方法在大多数情况下实现了具有竞争力或改进的性能，特别是在投影面积一致性和物理上合理的正反面对齐方面。此外，厚度感知约束和旋转假设评估降低了退化配置的风险，即两个表面被错误翻转但仍产生看似可接受的数值分数，从而支持对精细和薄型文化遗产文物的可靠非接触数字化。实现细节可在该 https URL 获取。
英文摘要
Non-contact three-dimensional reconstruction of thin, sheet-like heritage artifacts poses significant geometric and registration challenges. Due to their fragility, these artifacts cannot be suspended or equipped with artificial markers, necessitating independent acquisition of their front and back surfaces. Subsequent registration proves difficult due to the limited number of shared geometric features and the scarcity of explicit physical constraints, which may result in rotational ambiguity, instability, and structural collapse during iterative optimization. To address these challenges, we propose a geometry-constrained bidirectional point cloud registration method specifically tailored for thin, sheet-like heritage artifacts. The method integrates semantic-guided preprocessing, Principal Component Analysis (PCA)-based geometric normalization, and a thickness-aware registration strategy. The estimated physical thickness is incorporated as a geometric constraint to preserve structural integrity during registration. Rotational ambiguity is resolved by evaluating a finite set of global rotation hypotheses, each refined using the point-to-plane Iterative Closest Point (ICP) algorithm, with the optimal transformation selected via a geometry-aware fitness criterion consistent with the thickness scale. Experimental results show that the proposed method achieves competitive or improved performance in most cases, particularly in projected area consistency and physically plausible front-back alignment. In addition, the thickness-aware constraint and rotation hypothesis evaluation reduce the risk of degenerate configurations in which the two surfaces are incorrectly flipped while still yielding deceptively acceptable numerical scores, supporting reliable non-contact digitization of delicate and thin heritage artifacts. Implementation details are available at https://zyz-nwpu.github.io/GCBPCR/.
Comments26 pages, 8 figures. Accepted for publication in ACM Journal on Computing and Cultural Heritage
DOI：10.1145/3836772
