The problem of simultaneous rigid alignment of multiple unordered point sets which is unbiased towards any of the inputs has recently attracted increasing interest, and several reliable methods have been newly proposed. While being remarkably robust towards noise and clustered outliers, current approaches require sophisticated initialisation schemes and do not scale well to large point sets. This paper proposes a new resilient technique for simultaneous registration of multiple point sets by interpreting the latter as particle swarms rigidly moving in the mutually induced force fields. Thanks to the improved simulation with altered physical laws and acceleration of globally multiply-linked point interactions with a 2^D-tree (D is the space dimensionality), our Multi-Body Gravitational Approach (MBGA) is robust to noise and missing data while supporting more massive point sets than previous methods (with 10^5 points and more). In various experimental settings, MBGA is shown to outperform several baseline point set alignment approaches in terms of accuracy and runtime. We make our source code available for the community to facilitate the reproducibility of the results.
翻译:多个未定点组同时进行僵硬的对齐问题最近引起了越来越多的兴趣,而且提出了若干可靠的方法。虽然目前的方法对噪音和聚集外源非常活跃,但需要复杂的初始化计划,且不至于大点组。本文件建议采用一种新的弹性技术,将多点组同时登记,将后者解释为粒子群在相互引力场的僵硬移动。由于改进了模拟,改变了物理定律,加速了与2QD树(D是空间维度)的全球多点联系点互动,我们多功能引力法(MBGA)对噪音和缺失数据十分有力,同时支持比以往方法(10+5点和10+5点以上)更大规模的组合。在各种实验环境中,MBGA显示在精确度和运行时间方面超越了几个基准点。我们为社区提供了源代码,以促进结果的再生。