Yuanyuan F E N G, Hao L I, Chaokui L I, Jun C H E N
Hunan University of Science and Technology, School of Resource & Environment and Safety Engineering, Xiangtan, Hunan, 411201, China.
Hunan University of Science and Technology, National-Local Joint Engineering Laboratory of Geo-Spatial Information Technology, Xiangtan, Hunan, 411201, China.
Heliyon. 2024 Aug 19;10(17):e36529. doi: 10.1016/j.heliyon.2024.e36529. eCollection 2024 Sep 15.
The use of single-source data for real-world 3D modelling currently faces problems such as deformation, pulling and fuzzy texture at the bottom of buildings in some feature models because of the lack of images. Moreover, LIDAR generates a huge amount of data, and the massive raw data processing and point cloud parsing puts high demands on the hardware arithmetic and algorithms. Aiming at the deficiencies and defects of the two data sources of inclined photogrammetry and airborne laser point cloud in the construction of high-quality and high-precision city-level 3D models.
this study uses a university library building as an example and proposes the main technical process and method of modelling after fusing the point cloud data acquired by inclined photogrammetry and 3D laser scanning technology. This is accomplished in the reconstruction stage of multi-source data fusion through data spatial alignment, coordinate system unification and data spatial integration. At the stage of multi-source data fusion and reconstruction, through data spatial alignment, coordinate system unification, point cloud coarse alignment and the iterative closest point (ICP) algorithm, a realistic 3D model of a building is constructed to verify the effectiveness of the modelling method.
The method can effectively improve the accuracy of the real-life 3D model, repair the deficiencies in the model and optimise the details of the model. It can also significantly improve the fineness of the tilt photography model and perfectly present the geometric and texture information of the building, making it a superior method for fine 3D reconstruction.
This 3D reconstruction method of buildings, which integrates low-altitude inclined photogrammetry and airborne light detection and ranging (LiDAR), has high positional accuracy and can provide new methods and new ideas for the construction of digital campuses as well as for other engineering applications.
目前，在一些特征模型中，由于缺乏图像，使用单源数据进行真实世界的三维建模面临诸如建筑物底部变形、拉伸和纹理模糊等问题。此外，激光雷达会生成大量数据，海量原始数据的处理和点云解析对硬件运算能力和算法提出了很高要求。针对倾斜摄影测量和机载激光点云这两种数据源在高质量、高精度城市级三维模型构建中的不足与缺陷。
本研究以某大学图书馆建筑为例，提出了融合倾斜摄影测量和三维激光扫描技术获取的点云数据后进行建模的主要技术流程和方法。这在多源数据融合的重建阶段通过数据空间对齐、坐标系统一和数据空间整合来实现。在多源数据融合与重建阶段，通过数据空间对齐、坐标系统一、点云粗对齐和迭代最近点（ICP）算法，构建逼真的建筑物三维模型，以验证建模方法的有效性。
该方法能有效提高真实三维模型的精度，修复模型中的不足并优化模型细节。还能显著提高倾斜摄影模型的精细度，完美呈现建筑物的几何和纹理信息，使其成为精细三维重建的优越方法。
这种融合低空倾斜摄影测量和机载激光雷达的建筑物三维重建方法具有较高的定位精度，可为数字校园建设以及其他工程应用提供新方法和新思路。
