A 3D-2D Registration Method for Stereo Scan Overlay on Structure from Motion Model

Deepak Rajamohan, M. Garratt, M. Pickering
{"title":"A 3D-2D Registration Method for Stereo Scan Overlay on Structure from Motion Model","authors":"Deepak Rajamohan, M. Garratt, M. Pickering","doi":"10.1109/DICTA51227.2020.9363423","DOIUrl":null,"url":null,"abstract":"Ahstract- The ability to detect and analyze changes or understand the scene while navigating close to buildings is very important for autonomous aerial and ground vehicle based surveillance applications. For this, the latest textured 3D scan of the platform's view frustum has to be placed accurately in the context of a big map like a Structure from Motion (SfM) map of the region. However, due to the drift in the camera trajectory, the scans are usually not aligned with the SfM model. This paper proposes a novel registration algorithm that aligns the 3D scan using known 2D images of the SfM model. The proposed 3D-2D registration method uses a heuristic approach which first performs a robust 2D-2D registration between the projection of the 3D scan and the SfM images and then calculates the 3D alignment parameters by combining registration results of multiple camera views of the SfM model. The results presented compare the robustness of the proposed registration techniques with traditional approaches.","PeriodicalId":348164,"journal":{"name":"2020 Digital Image Computing: Techniques and Applications (DICTA)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 Digital Image Computing: Techniques and Applications (DICTA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DICTA51227.2020.9363423","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

Ahstract- The ability to detect and analyze changes or understand the scene while navigating close to buildings is very important for autonomous aerial and ground vehicle based surveillance applications. For this, the latest textured 3D scan of the platform's view frustum has to be placed accurately in the context of a big map like a Structure from Motion (SfM) map of the region. However, due to the drift in the camera trajectory, the scans are usually not aligned with the SfM model. This paper proposes a novel registration algorithm that aligns the 3D scan using known 2D images of the SfM model. The proposed 3D-2D registration method uses a heuristic approach which first performs a robust 2D-2D registration between the projection of the 3D scan and the SfM images and then calculates the 3D alignment parameters by combining registration results of multiple camera views of the SfM model. The results presented compare the robustness of the proposed registration techniques with traditional approaches.
运动模型结构立体扫描叠加的三维-二维配准方法
摘要:在建筑物附近导航时,检测和分析变化或理解场景的能力对于基于自主空中和地面车辆的监视应用非常重要。为此,平台视台的最新纹理3D扫描必须精确地放置在一个大地图的背景下,比如该地区的运动结构(SfM)地图。然而,由于相机轨迹的漂移,扫描通常不与SfM模型对齐。本文提出了一种新的配准算法,该算法使用已知的SfM模型的2D图像对3D扫描进行对齐。所提出的3D- 2d配准方法采用启发式方法,首先在3D扫描投影与SfM图像之间进行稳健的2D-2D配准,然后结合SfM模型的多个相机视图的配准结果计算3D对准参数。结果比较了所提出的配准技术与传统方法的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信