Robust Euclidean alignment of 3D point sets: the trimmed iterative closest point algorithm

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TEASER: Fast and Certifiable Point Cloud Registration (2020, background): “Multiple variants of ICP [62], [63], [64], [65], [66], [67], [68] have proposed to use robust cost functions to improve convergence.”
Three-Dimensional Face Recognition in the Presence of Facial Expressions: An Annotated Deformable Model Approach (2007, methodology): “Finally, if the resulting transformation is not satisfactory, we have an option of running the trimmed ICP algorithm [25].”
GDRNPP: A Geometry-Guided and Fully Learning-Based Object Pose Estimator (2021, unknown): “As for depth-based methods, the Iterative Closest Point (ICP) algorithm [72] and its variants [73], [74], [75], [76], [77] stand out as the predominant traditional pose reﬁnement algorithms.”
Fast and Robust Iterative Closest Point (2020, background): “A popular approach is to discard some point pairs from the alignment problem based on heuristics regarding their distance [5], [23], [24].”
Go-ICP: A Globally Optimal Solution to 3D ICP Point-Set Registration (2016, unknown): “Next, we will introduce the concept of an uncertainty radius as a mathematical preparation, then derive our bounds based on it.”
Image Matching from Handcrafted to Deep Features: A Survey (2020, background): “Numerous studies, such as EM-ICP (Granger and Pennec 2002), LM-ICP (Fitzgibbon 2003), and TriICP (Chetverikov et al. 2005), in the research field of PSR have been proposed to improve ICP.”