{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T23:05:19Z","timestamp":1779145519861,"version":"3.51.4"},"reference-count":53,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2023,7,14]],"date-time":"2023-07-14T00:00:00Z","timestamp":1689292800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["12075319"],"award-info":[{"award-number":["12075319"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["11805277"],"award-info":[{"award-number":["11805277"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51975583"],"award-info":[{"award-number":["51975583"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Inspired by the parallel visual pathway model of the human neural system, we propose an efficient and high-precision point cloud registration method based on complex network theory (PointCNT). A deep learning network (DNN) design method based on complex network theory is proposed, and a multipath feature extraction network, namely, Complex Kernel Point Convolution Neural Network (ComKP-CNN) for point clouds is designed based on the design method. Self-supervision is introduced to improve the feature extraction ability of the model. A feature embedding module is proposed to explicitly embed the transformation-variant coordinate information and transformation-invariant distance information into features. A feature fusion module is proposed to enable the source and template point clouds to perceive each other\u2019s nonlocal features. Finally, a Multilayer Perceptron (MLP) with prominent fitting characteristics is utilized to estimate the transformation matrix. The experimental results show that the Registration Recall (RR) of PointCNT on ModelNet40 dataset reached 96.4%, significantly surpassing one-stage methods such as Feature-Metric Registration (FMR) and approaching two-stage methods such as Geometric Transformer (GeoTransformer). The computation speed is faster than two-stage methods, and the registration run time is 0.15 s. In addition, ComKP-CNN is universal and can improve the registration accuracy of other point cloud registration methods.<\/jats:p>","DOI":"10.3390\/rs15143545","type":"journal-article","created":{"date-parts":[[2023,7,14]],"date-time":"2023-07-14T08:40:06Z","timestamp":1689324006000},"page":"3545","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["PointCNT: A One-Stage Point Cloud Registration Approach Based on Complex Network Theory"],"prefix":"10.3390","volume":"15","author":[{"given":"Xin","family":"Wu","sequence":"first","affiliation":[{"name":"National Key Lab of Aerospace Power System Safety and Plasma Technology, Air Force Engineering University, Xi\u2019an 710038, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6119-1400","authenticated-orcid":false,"given":"Xiaolong","family":"Wei","sequence":"additional","affiliation":[{"name":"National Key Lab of Aerospace Power System Safety and Plasma Technology, Air Force Engineering University, Xi\u2019an 710038, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haojun","family":"Xu","sequence":"additional","affiliation":[{"name":"National Key Lab of Aerospace Power System Safety and Plasma Technology, Air Force Engineering University, Xi\u2019an 710038, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Caizhi","family":"Li","sequence":"additional","affiliation":[{"name":"National Key Lab of Aerospace Power System Safety and Plasma Technology, Air Force Engineering University, Xi\u2019an 710038, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuanhan","family":"Hou","sequence":"additional","affiliation":[{"name":"National Key Lab of Aerospace Power System Safety and Plasma Technology, Air Force Engineering University, Xi\u2019an 710038, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yizhen","family":"Yin","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8381-2378","authenticated-orcid":false,"given":"Weifeng","family":"He","sequence":"additional","affiliation":[{"name":"National Key Lab of Aerospace Power System Safety and Plasma Technology, Air Force Engineering University, Xi\u2019an 710038, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,7,14]]},"reference":[{"key":"ref_1","unstructured":"Huang, X., Mei, G., Zhang, J., and Abbas, R. 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