CLIPPER+：一种用于鲁棒全局配准的快速最大团算法
CLIPPER+: A Fast Maximal Clique Algorithm for Robust Global Registration
AI总结：
CLIPPER+通过核心数剪枝缩小图规模，在保持较低运行时间的同时实现最高精度的最大团估计，用于离群点鲁棒的全局配准，可在超过99%关联为离群点的场景中成功配准点云。
摘要：
我们提出 CLIPPER+，一种在无权图中寻找最大团的算法，用于对离群点鲁棒的全局配准。配准问题可以表述为一个图，并通过寻找其最大团来求解。这种表述带来了对离群点的极端鲁棒性；然而，寻找最大团是一个 NP 难问题，因此在大规模问题中实际应用时需要近似。近似算法的性能通过其计算复杂度（运行时间越低越好）和解的精度（解与最大团的接近程度）来评估。相应地，CLIPPER+ 的主要贡献是在保持相对较低运行时间的同时，在精度上超越当前最先进的方法。CLIPPER+ 建立在先前工作（CLIPPER [1] 和 PMC [2]）的基础上，通过移除具有较小核心数且不可能成为最大团一部分的顶点来剪枝图。这将产生一个更小的图，在其上可以显著更快地估计最大团。我们在标准图基准以及合成和真实世界点云配准问题上评估了 CLIPPER+ 的性能。这些评估表明，CLIPPER+ 具有最高的精度，并且能够在超过 99% 的关联为离群点的场景中配准点云。我们的代码和评估基准发布在 https://github.com/ariarobotics/clipperp。
英文摘要：
We present CLIPPER+, an algorithm for finding maximal cliques in unweighted graphs for outlier-robust global registration. The registration problem can be formulated as a graph and solved by finding its maximum clique. This formulation leads to extreme robustness to outliers; however, finding the maximum clique is an NP-hard problem, and therefore approximation is required in practice for large-size problems. The performance of an approximation algorithm is evaluated by its computational complexity (the lower the runtime, the better) and solution accuracy (how close the solution is to the maximum clique). Accordingly, the main contribution of CLIPPER+ is outperforming the state-of-the-art in accuracy while maintaining a relatively low runtime. CLIPPER+ builds on prior work (CLIPPER [1] and PMC [2]) and prunes the graph by removing vertices that have a small core number and cannot be a part of the maximum clique. This will result in a smaller graph, on which the maximum clique can be estimated considerably faster. We evaluate the performance of CLIPPER+ on standard graph benchmarks, as well as synthetic and real-world point cloud registration problems. These evaluations demonstrate that CLIPPER+ has the highest accuracy and can register point clouds in scenarios where over $99\%$ of associations are outliers. Our code and evaluation benchmarks are released at https://github.com/ariarobotics/clipperp.
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