Mechanical School of Jiangsu University, Zhenjiang, Jiangsu Province, China.
Yangzhou Polytechnic Institute, Yangzhou, Jiangsu Province, China.
PLoS One. 2023 Nov 16;18(11):e0287134. doi: 10.1371/journal.pone.0287134. eCollection 2023.
In this research, we use hash match of invariants under fixed pair length and local compatibility check of positions or normal vectors to improve the efficiency of two-point normal set (2PNS) point cloud registration algorithm. On the one hand, we use the key value formed by the invariants of base point pairs of fixed length to construct and retrieve the hash table to realize the matching of base point pairs in the two point clouds to be registered to speed up the extraction of candidate transformation matrices. On the other hand, the time consumed in the verification phase is reduced by checking the compatibility between the positions or normal vectors of the corresponding points in the specific areas of the two point clouds under the transformation from the candidate matrix. Through these two improvements, the algorithm significantly reduces the time spent in the point cloud registration algorithm.
在这项研究中，我们使用固定对长不变量的哈希匹配和位置或法向量的局部兼容性检查来提高两点法向集（2PNS）点云配准算法的效率。一方面，我们使用固定长度基对点对不变量形成的关键值来构建和检索哈希表，以实现要注册的两个点云的基对点对的匹配，从而加速候选变换矩阵的提取。另一方面，通过检查候选矩阵变换下两个点云特定区域中对应点的位置或法向量之间的兼容性，减少验证阶段的时间消耗。通过这两个改进，该算法显著减少了点云配准算法所花费的时间。
