室内3D无人机跟踪的多模态数据集。

IF 6.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Scientific Data Pub Date : 2025-02-12 DOI:10.1038/s41597-025-04521-y
Jakub Rosner, Tomasz Krzeszowski, Adam Świtoński, Henryk Josiński, Wojciech Lindenheim-Locher, Michał Zieliński, Grzegorz Paleta, Marcin Paszkuta, Konrad Wojciechowski
{"title":"室内3D无人机跟踪的多模态数据集。","authors":"Jakub Rosner, Tomasz Krzeszowski, Adam Świtoński, Henryk Josiński, Wojciech Lindenheim-Locher, Michał Zieliński, Grzegorz Paleta, Marcin Paszkuta, Konrad Wojciechowski","doi":"10.1038/s41597-025-04521-y","DOIUrl":null,"url":null,"abstract":"<p><p>The subject of the paper is a multimodal dataset (DPJAIT) containing drone flights prepared in two variants - simulation-based and with real measurements captured by the gold standard Vicon system. It contains video sequences registered by the synchronized and calibrated multicamera set as well as reference 3D drone positions in successive time instants obtained from simulation procedure or using the motion capture technique. Moreover, there are scenarios with ArUco markers in the scene with known 3D positions and RGB cameras mounted on drones for which internal parameters are given. Three applications of 3D tracking are demonstrated. They are based on the overdetermined set of linear equations describing camera projection, particle swarm optimization, and the determination of the extrinsic matrix of the camera attached to the drone utilizing recognized ArUco markers.</p>","PeriodicalId":21597,"journal":{"name":"Scientific Data","volume":"12 1","pages":"257"},"PeriodicalIF":6.9000,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11821834/pdf/","citationCount":"0","resultStr":"{\"title\":\"Multimodal dataset for indoor 3D drone tracking.\",\"authors\":\"Jakub Rosner, Tomasz Krzeszowski, Adam Świtoński, Henryk Josiński, Wojciech Lindenheim-Locher, Michał Zieliński, Grzegorz Paleta, Marcin Paszkuta, Konrad Wojciechowski\",\"doi\":\"10.1038/s41597-025-04521-y\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The subject of the paper is a multimodal dataset (DPJAIT) containing drone flights prepared in two variants - simulation-based and with real measurements captured by the gold standard Vicon system. It contains video sequences registered by the synchronized and calibrated multicamera set as well as reference 3D drone positions in successive time instants obtained from simulation procedure or using the motion capture technique. Moreover, there are scenarios with ArUco markers in the scene with known 3D positions and RGB cameras mounted on drones for which internal parameters are given. Three applications of 3D tracking are demonstrated. They are based on the overdetermined set of linear equations describing camera projection, particle swarm optimization, and the determination of the extrinsic matrix of the camera attached to the drone utilizing recognized ArUco markers.</p>\",\"PeriodicalId\":21597,\"journal\":{\"name\":\"Scientific Data\",\"volume\":\"12 1\",\"pages\":\"257\"},\"PeriodicalIF\":6.9000,\"publicationDate\":\"2025-02-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11821834/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scientific Data\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.1038/s41597-025-04521-y\",\"RegionNum\":2,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Data","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41597-025-04521-y","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

本文的主题是一个多模态数据集(DPJAIT),其中包含两种变体的无人机飞行——基于模拟的和由金标准Vicon系统捕获的真实测量。它包含由同步和校准的多摄像机集注册的视频序列,以及从模拟程序或使用动作捕捉技术获得的连续时间瞬间的参考3D无人机位置。此外,在场景中有ArUco标记的场景,具有已知的3D位置和安装在无人机上的RGB相机,其内部参数是给定的。演示了三维跟踪的三种应用。它们基于描述相机投影的超确定线性方程组,粒子群优化以及利用识别的ArUco标记确定附着在无人机上的相机的外部矩阵。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

摘要图片

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Multimodal dataset for indoor 3D drone tracking.

The subject of the paper is a multimodal dataset (DPJAIT) containing drone flights prepared in two variants - simulation-based and with real measurements captured by the gold standard Vicon system. It contains video sequences registered by the synchronized and calibrated multicamera set as well as reference 3D drone positions in successive time instants obtained from simulation procedure or using the motion capture technique. Moreover, there are scenarios with ArUco markers in the scene with known 3D positions and RGB cameras mounted on drones for which internal parameters are given. Three applications of 3D tracking are demonstrated. They are based on the overdetermined set of linear equations describing camera projection, particle swarm optimization, and the determination of the extrinsic matrix of the camera attached to the drone utilizing recognized ArUco markers.

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
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
期刊最新文献
Chinese Food Images for Full-cycle Nutrition Analysis Towards Diabetes Management. Chromosome-level genome assembly of a citrus and tea insect pest, Aphis aurantii. Chromosome level genome assembly of the tea ash wood moth, Agriophara rhombata. Active acoustics data from the French PIRATA cruises in the tropical Atlantic, 2015-2025. Diploid chromosome-level genome assembly of the Amazonian endemic morning glory Ipomoea cavalcantei D.F. Austin.
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1