使用双目摄像头生成虚拟地面控制点

Drones Pub Date : 2024-05-12 DOI:10.3390/drones8050195

Ariel Vazquez-Dominguez, A. Magadán-Salazar, R. Pinto-Elías, J. Fuentes-Pacheco, Máximo López-Sánchez, Hernán Abaunza-González

{"title":"使用双目摄像头生成虚拟地面控制点","authors":"Ariel Vazquez-Dominguez, A. Magadán-Salazar, R. Pinto-Elías, J. Fuentes-Pacheco, Máximo López-Sánchez, Hernán Abaunza-González","doi":"10.3390/drones8050195","DOIUrl":null,"url":null,"abstract":"This paper presents a methodology for generating virtual ground control points (VGCPs) using a binocular camera mounted on a drone. We compare the measurements of the binocular and monocular cameras between the classical method and the proposed one. This work aims to decrease human processing times while maintaining a reduced root mean square error (RMSE) for 3D reconstruction. Additionally, we propose utilizing COLMAP to enhance reconstruction accuracy by solely utilizing a sparse point cloud. The results demonstrate that implementing COLMAP for pre-processing reduces the RMSE by up to 16.9% in most cases. We prove that VGCPs further reduce the RMSE by up to 61.08%.","PeriodicalId":507567,"journal":{"name":"Drones","volume":"105 44","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Generation of Virtual Ground Control Points Using a Binocular Camera\",\"authors\":\"Ariel Vazquez-Dominguez, A. Magadán-Salazar, R. Pinto-Elías, J. Fuentes-Pacheco, Máximo López-Sánchez, Hernán Abaunza-González\",\"doi\":\"10.3390/drones8050195\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a methodology for generating virtual ground control points (VGCPs) using a binocular camera mounted on a drone. We compare the measurements of the binocular and monocular cameras between the classical method and the proposed one. This work aims to decrease human processing times while maintaining a reduced root mean square error (RMSE) for 3D reconstruction. Additionally, we propose utilizing COLMAP to enhance reconstruction accuracy by solely utilizing a sparse point cloud. The results demonstrate that implementing COLMAP for pre-processing reduces the RMSE by up to 16.9% in most cases. We prove that VGCPs further reduce the RMSE by up to 61.08%.\",\"PeriodicalId\":507567,\"journal\":{\"name\":\"Drones\",\"volume\":\"105 44\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Drones\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/drones8050195\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Drones","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/drones8050195","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

本文介绍了一种利用安装在无人机上的双目摄像头生成虚拟地面控制点（VGCP）的方法。我们比较了经典方法和建议方法中双目和单目相机的测量结果。这项工作旨在减少人工处理时间，同时降低三维重建的均方根误差（RMSE）。此外，我们还建议利用 COLMAP，通过仅使用稀疏点云来提高重建精度。结果表明，在大多数情况下，使用 COLMAP 进行预处理最多可将 RMSE 降低 16.9%。我们证明，VGCP 可进一步降低 RMSE，最高可达 61.08%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Generation of Virtual Ground Control Points Using a Binocular Camera

This paper presents a methodology for generating virtual ground control points (VGCPs) using a binocular camera mounted on a drone. We compare the measurements of the binocular and monocular cameras between the classical method and the proposed one. This work aims to decrease human processing times while maintaining a reduced root mean square error (RMSE) for 3D reconstruction. Additionally, we propose utilizing COLMAP to enhance reconstruction accuracy by solely utilizing a sparse point cloud. The results demonstrate that implementing COLMAP for pre-processing reduces the RMSE by up to 16.9% in most cases. We prove that VGCPs further reduce the RMSE by up to 61.08%.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Drones

自引率

0.00%

发文量