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[1]辜第桢,杨耘*,赵波,等.GNSS拒止环境下基于共视图优化的无人机影像快速位姿估计与应急建图[J].地球科学与环境学报,2025,47(05):987-998.[doi:10.19814/j.jese.2025.01042]
　GU Di-zhen,YANG Yun*,ZHAO Bo,et al.Rapid Pose Estimation and Emergency Mapping for UAV Images Based on Common-view Optimization in GNSS-denied Environments[J].Journal of Earth Sciences and Environment,2025,47(05):987-998.[doi:10.19814/j.jese.2025.01042]
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GNSS拒止环境下基于共视图优化的无人机影像快速位姿估计与应急建图(PDF)
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《地球科学与环境学报》[ISSN:1672-6561/CN:61-1423/P]

卷:
第47卷
期数:
2025年第05期
页码:
987-998
栏目:
大地测量、遥感与地学大数据
出版日期:
2025-10-01

文章信息/Info

Title:
Rapid Pose Estimation and Emergency Mapping for UAV Images Based on Common-view Optimization in GNSS-denied Environments
文章编号:
1672-6561(2025)05-0987-12
作者:
辜第桢1; 杨耘1; 2*; 赵波3; 李祖锋4; 郝国朴1; 陈世昌1; 杨成生1; 唐一亮1
(1. 长安大学 地质工程与测绘学院,陕西 西安 710054; 2. 地理信息工程国家重点实验室,陕西 西安 710054; 3. 甘肃省地质矿产勘查开发局测绘勘查院,甘肃 兰州 730060; 4. 中国电建集团西北勘测设计研究院有限公司,陕西 西安 710065)
Author(s):
GU Di-zhen1;  YANG Yun1; 2*;  ZHAO Bo3;  LI Zu-feng4;  HAO Guo-pu1;  CHEN Shi-chang1;  YANG Cheng-sheng1;  TANG Yi-liang1
(1. School of Geological Engineering and Geomatics, Chang'an University, Xi'an 710054, Shaanxi, China; 2. State Key Laboratory of Geo-information Engineering, Xi'an 710054, Shaanxi, China; 3. Surveying and Exploration Institute of Geology and Mineral Exploration and Development of Gansu Provincial Bureau, Lanzhou 730060, Gansu, China; 4. Northwest Engineering Corporation Limited, PowerChina, Xi'an 710065, Shaanxi, China)
关键词:
无人机影像序列;  应急场景;  影像检索;  共视图;  特征匹配;  位姿估计;  运动恢复结构
Keywords:
UAV image sequence;  emergency scene;  image retrieval;  common-view graph;  feature matching;  pose estimation;  structure from motion
分类号:
P231
DOI:
10.19814/j.jese.2025.01042
文献标志码:
A
摘要:
针对全球导航卫星系统(GNSS)拒止环境下无人机影像位姿估计效率低的问题,提出一种基于共视图优化的快速建图算法——NSG-VLAD算法。首先,利用尺度不变特征变换(SIFT)提取每张影像的特征,并利用局部聚合描述子向量(VLAD)算法将特征描述子聚合为全局特征向量; 其次,利用基于图索引的近似最近邻搜索(ANNS)算法进行相似影像的检索; 最后,对各个相似影像对构建共视图,并进行迭代匹配,从而提升影像特征匹配、影像位姿估计及应急场景建图的效率。在此基础上,利用NPU_FACTORY、NPU_PARK数据集以及3个自制数据集,将NSG-VLAD算法与具有代表性的Colmap开源软件和Metashape、Pix4Dmapper商业软件进行对比验证。结果表明:NSG-VLAD算法较Metashape商业软件重建速度提高了3倍,比Colmap开源软件快10倍以上,重投影误差优于Colmap开源软件和Metashape商业软件; 在应急测绘任务下的三维点云建图速度高于同类方法至少2倍,验证了NSG-VLAD算法在地震灾害等GNSS拒止环境下的应急测绘中具有良好应用前景。
Abstract:
In order to improve the efficiency of UAV image pose estimation in GNSS-denied environments, a fast mapping algorithm based on common-view graph optimization is proposed, named as NSG-VLAD. First, scale invariant feature transform(SIFT)is employed to extract features from each image, and then the vector of locally aggregated descriptors(VLAD)algorithm is used to aggregate the feature descriptor into a global feature vector; subsequently, the graph-based approximate nearest neighbor search(ANNS)algorithm is utilized for retrieving similar images; finally, a common-view graph is constructed for each pair of similar images, followed by iterative matching, thereby enhancing the efficiency of image feature matching, pose estimation, and mapping in emergency scence. By utilizing NPU_FACTORY, NPU_PARK and three self-created datasets, NSG-VLAD algorithm is compared with the representative Colmap open-source software, as well as Metaphase and Pix4Dmapper commercial softwares. The results show that NSG-VLAD algorithm is 3 times higher than Metashape commercial software in image reconstruction, and 10 times faster than Colmap open-source software; re-projection error of NSG-VLAD algorithm surpasses that of Colmap open-source software and Metashape commercial software. The 3D point cloud mapping speed is at least 2 times faster than the similar methods in emergency surveying tasks, validating that NSG-VLAD algorithm has a good application prospect on emergency mapping in GNSS-denied environments such as earthquake disaster areas.

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备注/Memo

备注/Memo:
收稿日期:2025-01-23; 修回日期:2025-04-09
基金项目:陕西省教育厅科学研究计划服务地方专项项目(23JE002); 国家自然科学基金项目(42174032)
*通信作者:杨 耘(1975-),女,新疆沙湾人,长安大学副教授,工学博士,博士后,E-mail:yangyunbox@chd.edu.cn。
更新日期/Last Update: 2025-10-01