{"title":"3D Reconstruction of Point Clouds and Solid Models from LiDAR and Digital Stereo Images","authors":"Abu Kamara, S. Dogan","doi":"10.36287/setsci.4.6.059","DOIUrl":null,"url":null,"abstract":"One of the fastest 3D data acquisition methods is LiDAR scanning technology. By using LiDAR scanners, 3D point clouds of the scanned scene are obtained easily. Although the scanning phase is fast, the meaningful and effective 3D visualization of the scene requires the raw point cloud data to be processed in advanced levels. This paper aims at explaining those processing steps and comparison of the LiDAR technology to the state of the art methods. For this purpose, a building point clouds data obtained by a terrestrial LiDAR scanner was used. This paper explains the registration of point clouds data, its underlying concepts, mathematical models as well as the free open source libraries to be used to perform these operations. Despite the remarkable achievements in LiDAR technology and data processing, it is still a relatively young subject and would likely change its course rather quickly in the near future.","PeriodicalId":6817,"journal":{"name":"4th International Symposium on Innovative Approaches in Engineering and Natural Sciences Proceedings","volume":"137 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"4th International Symposium on Innovative Approaches in Engineering and Natural Sciences Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36287/setsci.4.6.059","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
One of the fastest 3D data acquisition methods is LiDAR scanning technology. By using LiDAR scanners, 3D point clouds of the scanned scene are obtained easily. Although the scanning phase is fast, the meaningful and effective 3D visualization of the scene requires the raw point cloud data to be processed in advanced levels. This paper aims at explaining those processing steps and comparison of the LiDAR technology to the state of the art methods. For this purpose, a building point clouds data obtained by a terrestrial LiDAR scanner was used. This paper explains the registration of point clouds data, its underlying concepts, mathematical models as well as the free open source libraries to be used to perform these operations. Despite the remarkable achievements in LiDAR technology and data processing, it is still a relatively young subject and would likely change its course rather quickly in the near future.