{"title":"Cad点云的三维刚性配准","authors":"Ammar Hattab, G. Taubin","doi":"10.1109/ICCSE1.2018.8373991","DOIUrl":null,"url":null,"abstract":"In this paper, we introduce a new method for the rough alignment of point-clouds. We focus on a special type of point-clouds that is composed of simple geometric shapes like planes, cylinders, cones, etc. We call them 3D CAD point clouds. They are usually used in industrial and mechanical applications. The proposed method starts by detecting basic shapes in the point-clouds. And then using them to find the best transformation (rotation and translation) that aligns the point- clouds. Then, we run the fine alignment step using the iterative closest point method (ICP). We show several real-world examples of point-clouds before and after the alignment using this method. The results suggest that the proposed method works well in most cases given enough overlap between the point-clouds.","PeriodicalId":383579,"journal":{"name":"2018 International Conference on Computing Sciences and Engineering (ICCSE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"3D Rigid Registration of Cad Point-Clouds\",\"authors\":\"Ammar Hattab, G. Taubin\",\"doi\":\"10.1109/ICCSE1.2018.8373991\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we introduce a new method for the rough alignment of point-clouds. We focus on a special type of point-clouds that is composed of simple geometric shapes like planes, cylinders, cones, etc. We call them 3D CAD point clouds. They are usually used in industrial and mechanical applications. The proposed method starts by detecting basic shapes in the point-clouds. And then using them to find the best transformation (rotation and translation) that aligns the point- clouds. Then, we run the fine alignment step using the iterative closest point method (ICP). We show several real-world examples of point-clouds before and after the alignment using this method. The results suggest that the proposed method works well in most cases given enough overlap between the point-clouds.\",\"PeriodicalId\":383579,\"journal\":{\"name\":\"2018 International Conference on Computing Sciences and Engineering (ICCSE)\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Computing Sciences and Engineering (ICCSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCSE1.2018.8373991\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Computing Sciences and Engineering (ICCSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSE1.2018.8373991","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we introduce a new method for the rough alignment of point-clouds. We focus on a special type of point-clouds that is composed of simple geometric shapes like planes, cylinders, cones, etc. We call them 3D CAD point clouds. They are usually used in industrial and mechanical applications. The proposed method starts by detecting basic shapes in the point-clouds. And then using them to find the best transformation (rotation and translation) that aligns the point- clouds. Then, we run the fine alignment step using the iterative closest point method (ICP). We show several real-world examples of point-clouds before and after the alignment using this method. The results suggest that the proposed method works well in most cases given enough overlap between the point-clouds.