S. Voronin, A. Vasilyev, V. Kober, A. Makovetskii, A. Voronin, Dmitrii Zhernov
{"title":"非一致点云配准的深度神经网络","authors":"S. Voronin, A. Vasilyev, V. Kober, A. Makovetskii, A. Voronin, Dmitrii Zhernov","doi":"10.1117/12.2677782","DOIUrl":null,"url":null,"abstract":"Recently, there has been essential progress in the field of deep learning, which has led to compelling advances in most of the semantic tasks of computer vision, such as classification, detection, and segmentation. Point cloud registration is a task that aligns two or more different point clouds by evaluating the relative transformation between them. The Iterative Closest Points (ICP) algorithm and its variants have relatively good computational efficiency but are known to be subject to local minima, so rely on the quality of the initialization. In this paper, we propose a neural network based on the Deep Closest Points (DCP) neural network to solve the point cloud registration problem for incongruent point clouds. Computer simulation results are provided to illustrate the performance of the proposed method.","PeriodicalId":434863,"journal":{"name":"Optical Engineering + Applications","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Deep neural network for incongruent point clouds registration\",\"authors\":\"S. Voronin, A. Vasilyev, V. Kober, A. Makovetskii, A. Voronin, Dmitrii Zhernov\",\"doi\":\"10.1117/12.2677782\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recently, there has been essential progress in the field of deep learning, which has led to compelling advances in most of the semantic tasks of computer vision, such as classification, detection, and segmentation. Point cloud registration is a task that aligns two or more different point clouds by evaluating the relative transformation between them. The Iterative Closest Points (ICP) algorithm and its variants have relatively good computational efficiency but are known to be subject to local minima, so rely on the quality of the initialization. In this paper, we propose a neural network based on the Deep Closest Points (DCP) neural network to solve the point cloud registration problem for incongruent point clouds. Computer simulation results are provided to illustrate the performance of the proposed method.\",\"PeriodicalId\":434863,\"journal\":{\"name\":\"Optical Engineering + Applications\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-10-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Optical Engineering + Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2677782\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Optical Engineering + Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2677782","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Deep neural network for incongruent point clouds registration
Recently, there has been essential progress in the field of deep learning, which has led to compelling advances in most of the semantic tasks of computer vision, such as classification, detection, and segmentation. Point cloud registration is a task that aligns two or more different point clouds by evaluating the relative transformation between them. The Iterative Closest Points (ICP) algorithm and its variants have relatively good computational efficiency but are known to be subject to local minima, so rely on the quality of the initialization. In this paper, we propose a neural network based on the Deep Closest Points (DCP) neural network to solve the point cloud registration problem for incongruent point clouds. Computer simulation results are provided to illustrate the performance of the proposed method.