摘要
近几年来,基于无人机倾斜摄影影像的三维重建技术已是摄影测量与计算机视觉领域的研究热点,已被广泛应用于大比例尺地形图生产以及智慧城市等领域。针对无人机倾斜影像的数据高冗余、时间与空间复杂度高等问题,本文提出了一种快速有效的无人机序列影像三维重建方法。选择南水北调中线工程开放场景某一段的序列无人机影像,在不辅助POS等其他定位信息的基础上,仅依靠重叠影像间的匹配结果划定影像分区;在单独分区内采用改进的增量式SFM方法进行三维重建;最后再将各个分区依据分区间的重叠信息进行合并,完成整个测区的三维重建,并与商业建模软件以及传统的计算机视觉三维重建方法对比。结果表明,该方法在保持高精度的同时可以大幅提高重建效率,重建速度可提升5倍以上,尤其适用于大场景大规模数据集。
In recent years,3D reconstruction technology based on UAV tilted photographic images has been a research hotspot in the field of photogrammetry and computer vision,and has been widely used in the production of large-scale topographic maps as well as in the field of smart cities.In view of the problems of high data redundancy and high time and space complexity of UAV tilted images,this paper proposes a fast and effective 3D reconstruction method for UAV sequence images.Sequential UAV images of a section of the open scene of the Middle Route of the South to North Water Transfer Project were selected to delineate the image zones by relying only on the matching results among the overlapping images without assisting other localization information such as POS.The improved incremental SFM method is used for 3D reconstruction within individual partitions,and finally each partition is merged based on the overlapping information between partitions to complete the 3D reconstruction of the entire survey area.It is compared with commercial modeling software and traditional computer vision 3D reconstruction methods.The results show that the method can significantly improve the reconstruction efficiency while maintaining high accuracy,and the reconstruction speed can be improved by more than 5 times,which is especially suitable for large-scale datasets with large scenes.
作者
宋书学
孙统领
刘文锴
胡青峰
高英
邹根中
王鹏
SONG Shuxue;SUN Tongling;LIU Wenkai;HU Qingfeng;GAO Ying;ZOU Genzhong;WANG Peng(China South-to-North Water Diversion Middle Route Corporation Limited,Nanyang 473000,China;College of Surveying and Geo-informatics,North China University of Water Resources and Electric Power,Zhengzhou 450046,China;Henan Water&Power Engineering Consulting Co.,Ltd.,Zhengzhou 450016,China;Henan Jialu River Environmental Comprehensive Treatment Co.,Ltd.,Zhengzhou 450002,China)
出处
《华北水利水电大学学报(自然科学版)》
北大核心
2024年第1期31-36,共6页
Journal of North China University of Water Resources and Electric Power:Natural Science Edition
基金
国家自然科学基金项目(42277478)。