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However, challenges arise due to the uncertainty in 3D key point detection techniques and the similarity of local surface features. These factors often lead to feature descriptors establishing correspondences containing significant outliers. Current point cloud registration algorithms are typically hindered by these outliers, affecting both their efficiency and accuracy. In this paper, we propose a fast and robust point cloud registration method based on a compatibility graph and accelerated guided sampling. By constructing a compatible graph with correspondences, a minimum subset sampling method combining compatible edge sampling and compatible vertex sampling is proposed to reduce the influence of outliers on the estimation of the registration parameters. Additionally, an accelerated guided sampling strategy based on preference scores is presented, which effectively utilizes model parameters generated during the iterative process to guide the sampling toward inliers, thereby enhancing computational efficiency and the probability of estimating optimal parameters. Experiments are carried out on both synthetic and real-world data. The experimental results demonstrate that our proposed algorithm achieves a significant balance between registration accuracy and efficiency compared to state-of-the-art registration algorithms such as RANSIC and GROR. Even with up to 2000 initial correspondences and an outlier ratio of 99%, our algorithm achieves a minimum rotation error of 0.737\u00b0 and a minimum translation error of 0.0201 m, completing the registration process within 1 s.<\/jats:p>","DOI":"10.3390\/rs16152789","type":"journal-article","created":{"date-parts":[[2024,7,30]],"date-time":"2024-07-30T15:25:23Z","timestamp":1722353123000},"page":"2789","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Fast Robust Point Cloud Registration Based on Compatibility Graph and Accelerated Guided Sampling"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8848-8156","authenticated-orcid":false,"given":"Chengjun","family":"Wang","sequence":"first","affiliation":[{"name":"ZNDY of Ministerial Key Laboratory, Nanjing University of Science and Technology, Nanjing 210094, China"},{"name":"School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8902-9357","authenticated-orcid":false,"given":"Zhen","family":"Zheng","sequence":"additional","affiliation":[{"name":"ZNDY of Ministerial Key Laboratory, Nanjing University of Science and Technology, Nanjing 210094, China"},{"name":"School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bingting","family":"Zha","sequence":"additional","affiliation":[{"name":"ZNDY of Ministerial Key Laboratory, Nanjing University of Science and Technology, Nanjing 210094, China"},{"name":"School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haojie","family":"Li","sequence":"additional","affiliation":[{"name":"ZNDY of Ministerial Key Laboratory, Nanjing University of Science and Technology, Nanjing 210094, China"},{"name":"School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,7,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Han, T., Zhang, R., Kan, J., Dong, R., Zhao, X., and Yao, S. 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