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地面激光扫描联合无人机影像的三维模型重建研究

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针对无人机影像在复杂环境(如地面植被茂密区域和城区高楼密集区)中获取精确三维信息面临的挑战,采用地面激光扫描联合无人机影像技术,提出了在此类复杂区域的高质量三维模型重建方法.采用无人机、地面激光扫描仪,获取了河南城建学院5 号教学楼的影像信息和点云数据.通过单点配准算法,在地面激光点云和无人机影像点云中寻找并匹配同名特征点,形成了完整的点云数据.采用双向KD-tree优化的ICP算法,重建了5 号教学楼的三维实景模型,并对其精度进行了定量、定性分析.结果表明,与无人机影像相比,采用激光扫描联合无人机影像技术获取的三维模型精细程度高,能够准确地反映研究区域的地形地貌和建筑物结构.模型点位中误差为0.039 m,达到了厘米级,满足实际应用中的精度要求.
3 D model reconstruction using ground laser scanning and drone imagery
In response to the challenges of obtaining accurate three-dimensional information from drone imagery in complex environments,such as densely vegetated ground areas and city centers with tall buildings,a method for high-quality three-dimensional model reconstruction in such complex areas is proposed using a combination of ground laser scanning and drone imagery technology.Imagery information and point cloud data of Building No.5 at Henan University of Urban Construction were obtained using drones and ground laser scanners.By em-ploying a single-point registration algorithm,named feature points were identified and matched between the ground laser point cloud and the drone imagery point cloud,forming a complete point cloud dataset.The ICP algorithm optimized by bidirectional KD-tree was utilized to reconstruct the three-dimensional realistic model of Building No.5,and its accuracy was analyzed both quantitatively and qualitatively.The results demonstrate that the three-dimensional model obtained using the integrated laser scanning and drone imagery technology is more detailed compared to that obtained from drone imagery alone,accurately reflecting the terrain and building structures of the study area.The model′s point position mean error is 0.039 m,achieving a centimeter-level precision that meets the accuracy requirements for practical applications.

ground laser scanningdrone imagery3D model reconstructiondata fusion

柏春岚、张志国、刘豪

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河南城建学院 测绘与城市空间信息学院,河南 平顶山 467036

中国三冶集团有限公司 建筑制品工程公司,辽宁 鞍山 114000

河南城建学院 电气与控制工程学院,河南 平顶山 467036

地面激光扫描 无人机影像 三维模型重建 数据融合

2024

河南城建学院学报
河南城建学院

河南城建学院学报

影响因子:0.457
ISSN:1674-7046
年,卷(期):2024.33(6)